eyesweb 5.0.3 gesture processing user manual
DESCRIPTION
The EyesWeb Expressive Gesture Processing Library includes a collection of softwaremodules and patches (interconnections of modules) contained ....TRANSCRIPT
EyesWeb XMI 5.0.3.0 – Expressive Gesture processingLibrary
July 30, 2009
Part I
Description
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The EyesWeb Expressive Gesture Processing Library includes a collection of softwaremodules and patches (interconnections of modules) contained ....
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Part II
Reference
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Chapter 1
Gesture Processing Catalog
1.1 Blocks
1.1.1 Add point
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class name Add pointcatalog name Gesture Processingcatalog id EywGPclass id AddPointauthors Gualtiero Volpe
This block appends the input point to the input trajectory.
Inputs
Input trajectoryid InputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read writereferred as inplace Output trajectoryreferred as inherited *no*
The trajectory to which the input point has to be added.
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Input pointid InputPointtype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The point to be added to the input trajectory.
Outputs
Output trajectoryid OutputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatypeinplace id Input trajectoryinherited id *no*
The output trajectory including the added point.
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1.1.2 Blob ellipse
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class name Blob ellipsecatalog name Gesture Processingcatalog id EywGPclass id BlobEllipseauthors Gualtiero Volpe
This block generates an elliptical approximation of a blob. From such ellipse it is possibleto obtain an estimate of parameters such as blob orientation and contraction/expansion.
Inputs
Input imageid InputImagetype Base, Blob 2Dtype id base, blob2d
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input image containing the blob to be approximated by an ellipse. It must be ablack & white image.
Outputs
Output ellipseid OutputEllipsetype Base, Ellipse 2D doubletype id base, ellipse 2d doubleinplace id *no*inherited id *no*
The ellipse approximating the input block.
Output ellipseid OutputCentertype Base, Graphic Point 2D doubletype id base, graphic point 2d doubleinplace id *no*inherited id *no*
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The ellipse approximating the input block.
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1.1.3 Contraction Index
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class name Contraction Indexcatalog name Gesture Processingcatalog id EywGPclass id ContractionIndexauthors Gualtiero Volpe
This block computes the Contraction Index (CI) of a blob.
Inputs
Input blobid InputBlobtype Base, Blob 2Dtype id base, blob2d
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input blob whose Contraction Index has to be computed.
Outputs
Contraction Indexid OutputIndextype Kernel, Double datatype (Kernel Catalog).type id kernel, doubleinplace id *no*inherited id *no*
The computed Contraction Index.
Parameters
Contraction Indexid ComputeBlobCItype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Contraction Index
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MinHeightRectid ComputeMinHeightRectRatiotype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
MinWidthRectid ComputeMinWidthRectRatiotype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Compute Eccentricityid ComputeEllipseEccentricitytype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Resetid Resettype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
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1.1.4 ConvexHull
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class name ConvexHullcatalog name Gesture Processingcatalog id EywGPclass id convexhullcomputation
Computes the convex hull of the input contour.
Inputs
Input contourid ConvexHullInContourtype Gesture Processing, Integer 2D Graphic Contourtype id EywGP, IntGraphicContour
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
A contour. This block computes the convex hull of the input contour
Outputs
The convex hullid ConvexHullOutConvexHulltype Base, Graphic Polygon 2D inttype id base, graphic polygon 2d intinplace id *no*inherited id *no*
This is the convex hull computed by the block
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1.1.5 Empty trajectory
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class name Empty trajectorycatalog name Gesture Processingcatalog id EywGPclass id EmptyTrajectoryGeneratorauthors Gualtiero Volpe
This block generates an empty trajectory.
Outputs
Output trajectoryid OutputTrajectorytype Gesture Processing, Integer 2D Geometric Trajectorytype id EywGP, IntGeometricTrajectory2Dinplace id *no*inherited id *no*
The generated trajectory. It will be an empty trajectory.
Parameters
Trajectory typeid TrajectoryTypetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:Geometric Integer 2DGeometric Real 2DGraphic Integer 2DGraphic Real 2DGeometric Integer 3DGeometric Real 3D
domain [ 0, 6 )The type of trajectory to be generated. It may be 2D, 3D or nD, geometric or graphical,
interger or real.
Trajectory labelid Labeltype Kernel, String datatype (Kernel Catalog).type id kernel, string
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The label of the generated 2D trajectory.
Sampling rateid SamplingRatetype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The sampling rate in Hz at which the trajectory is generated and its points are sampled.
Is maximum of points fixed?id IsSizeFixedtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Initialization matrix parameter is added to the block and displayed.The potential function will be initialized according to the values contained in the matrixprovided for the Initialization matrix parameter. Otherwise the potential function is ini-tialized with zeros. The default value is false.
Maximum number of pointsid MaxSizetype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 2, +infinity )
The maximum number of points in the generated trajectory. This parameter is availableonly if the maximum number of points is fixed.
Resetid Resettype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
Reset the generated trajectory by removing all its points.
Colorid Colortype Kernel, RGBColor datatype (Kernel Catalog).type id kernel, rgbcolor
The color of the generated trajectory. The value of this parameter is taken into accountonly if the generated trajectory is a graphic trajectory.
Thicknessid Thicknesstype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The thickness of the generated trajectory. The value of this parameter is taken intoaccount only if the generated trajectory is a graphic trajectory.
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1.1.6 Extract contours
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class name Extract contourscatalog name Gesture Processingcatalog id EywGPclass id ExtractContoursauthors Gualtiero Volpe
This block extracts the contours of the blobs detected in the input image. It returnsthe (x,y) coordinates of all the points in the extracted contours.
Inputs
Input imageid InputBlobtype Base, Blob 2Dtype id base, blob2d
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input image containing the blobs whose contours have to be extracted.
Outputs
Extracted contoursid ExtractedContourstype Kernel, Labelled settype id kernel, labeled setinplace id *no*inherited id *no*
The extracted contours of the blobs detected in the input image.
Parameters
Extract contoursid ExtractContourstype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Extract contours
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Extract outer contourid ExtractOuterContourstype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Extract outer contour
Contour typeid ContourTypetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:Geometric Integer 2DGeometric Real 2DGraphic Integer 2DGraphic Real 2D
domain [ 0, 4 )Specifies the type of data used for the output contour
Minimum number of pointsid MinNumOfPointstype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
The minimum number of points for a contour in order to be considered.
Approximation methodid ApproxMethodtype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:NoneSimpleTC89 L1TC89 KCOS
domain [ 0, 4 )The approximation method to be used for extracting contours.
Colorid Colortype Kernel, RGBColor datatype (Kernel Catalog).type id kernel, rgbcolor
The color of the generated trajectory. The value of this parameter is taken into accountonly if the generated trajectory is a graphic trajectory.
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Thicknessid Thicknesstype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The thickness of the generated trajectory. The value of this parameter is taken intoaccount only if the generated trajectory is a graphic trajectory.
IsFilledid IsFilledtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Specifies whether the contour has to be filled
FillColorid FillColortype Kernel, RGBColor datatype (Kernel Catalog).type id kernel, rgbcolor
Specifies the color to be used to fill the contour
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1.1.7 GeneralisedAutoCorrelation
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class name GeneralisedAutoCorrelationcatalog name Gesture Processingcatalog id EywGPclass id generalised auto correlationauthors Paolo Coletta
Computes the Generalised Auto-Correlation function from a static time-series. For de-tails about the Generalised Auto-Correlation function see ”Recurrence plots for the analysisof complex systems” by Norbert Marwan, M. Carmen Romano, Marco Thiel, and JurgenKurths; in Physics Reports 438 (2007), pages 237-329. This block implements equation(50) pag. 265 or equivalently (111) pag. 289. The value of epsilon is user-specified, N isthe buffer-size of the input time-series. The user can specify both a specific value for tauor a range. In the first case the output is a scalar number which gives the value of theauto-correlation for the given tau and epsilon; in the second case the output is the functionRR(tau).
Inputs
Input signalid inputtype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
Input signal on which to compute the generalised auto-correlation; the input signalshould implement the IStaticTimeSeries interface.
Required interfacesKernel, StaticTimeSeries
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Outputs
RR function of Tauid output function of tautype Kernel, Double matrix.type id kernel, double-matrixinplace id *no*inherited id *no*
This output represents the value of the function RR for each possible Tau in the user-specified domain
Parameters
Epsilonid epsilontype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Specifies the upper bound of the distance of two near points. I.e., two point are consid-ered to be one near the other one if their distance is belowe this threashold. The value ofR in the sum is 1 for near points.
Output typeid parameter output typetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layoutCombo Box:ScalarFunction Of Tau
domain [ 0, 2 )Specifies whether the output is a Scalar value, which represents the value of RR(epsilon,tau)
for for given values of epsilon and tau, or a Function, which represent the value of RR(epsilon,*)for a given value of epsilon and all possible values of tau
Tau Minid parameter tau mintype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
This parameter represents the minimum value of tau for which the output functionRR(tau) is computed
Tau Spreadid parameter tau spreadtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
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This parameter represents the spread of tau, i.e., tau is asusmed to be in the range [TauMin, Tau Min + Tau Spread]. This determines the size of the output function of tau.
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1.1.8 Geometric Trajectory from points
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class name Geometric Trajectory from pointscatalog name Gesture Processingcatalog id EywGPclass id GeometricTrajectoryFromPointsauthors Gualtiero Volpe
This block generates a trajectory conisting of the temporal sequence of the points pro-vided as input.
Inputs
Input 2D point.id InputPointtype Base, Graphic Labelled Set 2D inttype id base, graphic labeled set 2d int
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input 2D point to be added to the generated trajectory.
Outputs
Output 2D trajectoryid OutputTrajectorytype Base, Graphic Labelled Set 2D inttype id base, graphic labeled set 2d intinplace id *no*inherited id *no*
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Parameters
Trajectory typeid TrajectoryTypetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:Geometric Integer 2DGeometric Real 2DGraphic Integer 2DGraphic Real 2DGeometric Integer 3DGeometric Real 3D
domain [ 0, 6 )The type of trajectory to be generated. It may be 2D, 3D or nD, geometric or graphical,
interger or real.
Trajectory labelid Labeltype Kernel, String datatype (Kernel Catalog).type id kernel, string
The label of the generated 2D trajectory.
Sampling rateid SamplingRatetype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The sampling rate in Hz at which the input points are sampled.
Is maximum of points fixed?id IsSizeFixedtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Set this parameter to true if the maximum number of points belonging to the trajectoryis fixed. When such number is reached the oldest points are removed from the trajectory.
Maximum number of pointsid MaxSizetype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 2, +infinity )
The maximum number of points in the generated trajectory. This parameter is availableonly if the maximum number of points is fixed.
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Resetid Resettype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
Reset the generated trajectory by removing all its points.
Colorid Colortype Kernel, RGBColor datatype (Kernel Catalog).type id kernel, rgbcolor
The color of the generated trajectory. The value of this parameter is taken into accountonly if the generated trajectory is a graphic trajectory.
Thicknessid Thicknesstype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The thickness of the generated trajectory. The value of this parameter is taken intoaccount only if the generated trajectory is a graphic trajectory.
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1.1.9 Get kinematical features
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class name Get kinematical featurescatalog name Gesture Processingcatalog id EywGPclass id GetKinematicalFeaturesauthors Gualtiero Volpe
This block computes kinematical features (e.g., velocity, acceleration) on the input tra-jectory.
Inputs
Input trajectoryid InputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The trajectory to which the input point has to be added.
Outputs
Output trajectoryid OutputFeaturetype Kernel, Generic datatypetype id kernel, generic datatypeinplace id *no*inherited id *no*
The output trajectory including the added point.
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Parameters
Featureid FeatureToExtracttype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:VelocityAccelerationDirection
domain [ 0, 3 )The kinematical feature to be extracted.
Numeric derivativeid NumericDerivativetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layoutCombo Box:Backward differenceCentral difference
domain [ 0, 2 )The numeric derivative algorithm to be applied.
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1.1.10 Get point
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class name Get pointcatalog name Gesture Processingcatalog id EywGPclass id GetPointauthors Gualtiero Volpe
This block retrieves the required point from the input trajectory. Note that the pointis not removed from the trajectory.
Inputs
Input trajectoryid InputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input trajectory from where the indicated point will be retrieved.
Outputs
Output pointid OutputPointtype Kernel, Generic datatypetype id kernel, generic datatypeinplace id *no*inherited id *no*
The retrieved output point.
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Parameters
Point to extractid GetPointModetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:Get latest pointGet oldest pointGet point with index
domain [ 0, 3 )Indicate here which point you want to extract: the latest, the oldest, or a point to be
identified by its numerical index.
Indexid Indextype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 0, +infinity )
The index of the point to be retrieved. It ranges from 0 to the current size of thetrajectory - 1. This parameter is enabled only if the ”Point to extract” parameter is set to”Get point with index”.
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1.1.11 Get properties
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class name Get propertiescatalog name Gesture Processingcatalog id EywGPclass id GetTrajectoryPropertiesauthors Gualtiero Volpe
This block retrives and returns the properties (e.g., label, sampling rate, number ofpoints) of the input trajectory.
Inputs
Input trajectoryid InputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input trajectory whose propeties have to be retrieved and returned.
Outputs
Number of pointsid Sizetype Kernel, Int datatype (Kernel Catalog).type id kernel, intinplace id *no*inherited id *no*
The current number of points in the input trajectory.
Parameters
Return potential matrixid OutputTypetype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
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If set to true the Potential function output becomes available and the whole potentialmatrix is returned by the block. The default value is true..
Return hit regionsid OutputLabeltype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Hit regions output becomes available and a vector is returned, whereeach item is set to 0 if the corresponding region is missed or to 1 if the corresponding regionis hit. The default value is false.
Return indexes of hit regionsid OutputSamplingRatetype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true the Hit regions indexes output becomes available and a list of indexes ofhit regions is returned by the block. The default value is false.
Return region valuesid OutputIsSizeFixedtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Region values output becomes available and a vector is returned,where each item is set to the current potential value for the corresponding region. Thedefault value is false.
Return region valuesid OutputSizetype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Region values output becomes available and a vector is returned,where each item is set to the current potential value for the corresponding region. Thedefault value is false.
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1.1.12 Get trajectory features
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class name Get trajectory featurescatalog name Gesture Processingcatalog id EywGPclass id GetTrajectoryFeaturesauthors Gualtiero Volpe
This block retrives and returns features (e.g., lenght, directness index) of the inputtrajectory.
Inputs
Input trajectoryid InputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input trajectory whose features have to be computed.
Outputs
Output featureid OutputFeaturetype Kernel, Double datatype (Kernel Catalog).type id kernel, doubleinplace id *no*inherited id *no*
The computed output feature.
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Parameters
Feature to extractid FeatureToExtracttype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layoutCombo Box:LengthDirectness index
domain [ 0, 2 )The feature to be extracted.
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1.1.13 Hit Cell Detector
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class name Hit Cell Detectorcatalog name Gesture Processingcatalog id EywGPclass id HitCellDetectorauthors Gualtiero Volpe
Given a model in which a 2D space is divided in cells, this block computes the cellsoccupied (hit) by the current input points.
Inputs
Input positionsid InputPositionstype Kernel, Listtype id kernel, list
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The (x, y) coordinates of the input positions.
Outputs
Hit cellsid HitCellstype Kernel, Listtype id kernel, listinplace id *no*inherited id *no*
The (i, j) indexes of the hit cells corresponding to the current input positions.
Parameters
Cells along xid CellsXtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
The number of cells in which the input space has to be divided along the x dimension.
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Cells along yid CellsYtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
The number of cells in which the input space has to be divided along the y dimension.
Minimum along xid XMintype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The minimum input value along the x dimension.
Maximum along xid XMaxtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The maximum input value along the x dimension.
Minimum along yid YMintype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The minimum input value along the y dimension.
Maximum along yid YMaxtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The maximum input value along the y dimension.
Clip valuesid ClipValuestype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set, out of range values are clipped to the provided maximum and minimum values.Otherwise a warning message is displayed and the hit cell is not computed.
Clear input listid ClearListtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set, the input list is cleared after the computation of the hit cells.
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Quantization algorithmid QuantAlgtype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layoutCombo Box:Linear uniform
domain [ 0, 1 )The quantization algorithm to be employed for computing the hit cell.
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1.1.14 Hit Region Detector
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class name Hit Region Detectorcatalog name Gesture Processingcatalog id EywGPclass id HitRegionDetectorauthors Gualtiero Volpe
Given a model in which a 2D space is divided in cells, this block computes which regions(groups of cells) are occupied (hit) by the silhouette of a blob provided as input. Regionsare defined through a mask provided as parameter. Cells correspond to pixels in the imagefrom which the blob silhouette is extracted.
Inputs
Input imageid InputImagetype Base, Imagetype id base, image
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
An image containing the silhouette of a blob. The block will compute which regions inthe 2D space the input blob occupies (hits). The input image must be black and white,single channel, and have 8-bit depth.
Outputs
Hit regionsid OutputListtype Kernel, Listtype id kernel, listinplace id *no*inherited id *no*
A list of integer numbers. Such numbers are the indexes of regions the input bloboccupies (hits). The indexes are defined in the mask provided as parameter.
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Parameters
Maskid Masktype Kernel, Integer matrix.type id kernel, int-matrix
An integer matrix containing the indexes (identifiers) of the regions defined in the space.Items labeled with the same index (integer value) belong to the same region. The rangeof such indexes is [0, MaxNumOfRegions -1] where MaxNumOfRegions is the maximumnumber of regions that can be defined. The block considers as maximum number of regionsthe size of the Thresholds vector (see below). The mask matrix should have the samedimensions of the image from which the silhouette of the input blob has been extracted.The default dimensions are 288 rows and 352 columns; the default value is a matrix ofzeros.
Thresholdsid Thresholdstype Kernel, Integer matrix.type id kernel, int-matrix
An integer vector containing the thresholds to be applied to the occupation values ofeach region. Each item is the threshold for the corresponding region. A region is consideredto be hit if the number of its cells the input blob occupies exceeds this threshold. The blockconsiders the size of this vector as the maximum number of regions that can be defined.The default dimensions are 1 row and 256 columns (corresponding to the definition of 256cells). The default value is a vector of zeros.
Return occupation valuesid OutOccValuestype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true the block returns both the list of the indexes (identifiers) of the hit regionsand, separately, the list of the indexes and of the occupation values of the hit regions.Otherwise the list of the indexes of the hit regions only is returned. The default value isfalse.
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1.1.15 InternalQuantityOfMotion
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class name InternalQuantityOfMotioncatalog name Gesture Processingcatalog id EywGPclass id quantity of motion
Calculate internal quantity of motion. The measuring reguards internal modifications ofthe silhouette. The algortihm needs both image and blob input.ERROR AND WARNINGMESSAGE. - During initialization phase: - Matrix and image must be the same dimension:if the dimension of the matrix of weight and the dimension of the image are different. -Block Internal QOM : The mask or the anchor size are invalid: if the dimensions of medianfilter are not odd. - During execution phase: - Ipp library info: ippiv81.lib 5.2 5.2.108.410-Ipp Error description : Invalid mask size.
Inputs
input blobid input blobtype Base, Blob 2Dtype id base, blob2d
requiredrequired for initializationrequired for execution
read only/read write read writereferred as inplace *no*referred as inherited *no*
This is the blob extracted from the input image. Actually the block works only with asingle blob.
input imageid input imagetype Base, Imagetype id base, image
requiredrequired for initializationrequired for execution
read only/read write read writereferred as inplace *no*referred as inherited *no*
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Input image.
Outputs
output qomid output qomtype Kernel, Double datatype (Kernel Catalog).type id kernel, doubleinplace id *no*inherited id *no*
Quantity of internal motion. The output represents the number of nonzero pixels ofQOM image. If the parameter ’type’ is set to int, then the output is the number of pixels.If it is set to double the output is normalized according to ’Normalization Type’ parameter
output imageid output imagetype Base, Imagetype id base, imageinplace id *no*inherited id *no*
The image represents differents beetween the first and the last image of a dynamicqueue. The lenght of the queue is expressed by the parameter ’Window lenght’
Parameters
Weightid output qomtype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:EuclideaEuclidea InversaFrom MatrixFrom Matrix InverseNone
domain [ 0, 5 )The parameter represent the type of weight. Euclidean: the weight of pixels is the
distance from the baricenter. Inverse Euclidean: the weight of pixels is the inverse of thedistance from the baricenter. From Matrix: weights of pixels are stored in the matrix .Inverse From Matrix: weight of pixels are the inverse of the matix. None: There is noweight for each pixel.
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WindowLenghtid window lenghttype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 0, +infinity )
The size of a dynamic queue. The queue stores images and the algorithm process thefirst and the last image in the buffer.
Thresholdid thresholdtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The threshold used in the binarization of image.
Resetid resettype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
Reset the method and clear the queue of images. When reset button is pressed thealgorithmneeds to read ’Window lenght’ images.
MedianOnOffid mediantype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Active median filter.
MedianXid median xtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 0, +infinity )
The width of median filter mask used in the method
MedianYid median ytype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 0, +infinity )
The height of median filter mask used in the method
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Typeid output qom typetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layoutCombo Box:IntDouble
domain [ 0, 2 )Type of QOM. If it’s set to int value then the output is the number of non zero pixels in
the output image. If it’s set to double value the output is the normalization of the numberof non zero pixels according to the parameter Normalization Type.
Normalization Typeid norm qomtype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:AreaofImageAreaofBoundingRectangleAreaofBlob
domain [ 0, 3 )It specifies if the numeric output is normalized by the area of entire image, by the area
of the bounding rectangle or by the area of the blob.
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1.1.16 Motion duration
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class name Motion durationcatalog name Gesture Processingcatalog id EywGPclass id MotionDurationauthors Gualtiero Volpe
This block computes the time duration of pause and motion phases starting from asegmentation signal provided as input.
Inputs
Input segmentation signalid SegmentationSignaltype Kernel, Double datatype (Kernel Catalog).type id kernel, double
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input segmentation signal. It should be 0 during pause phases and different from0 during motion phases.
Outputs
Motion durationid MotionDurationtype Kernel, Double datatype (Kernel Catalog).type id kernel, doubleinplace id *no*inherited id *no*
The duration of the last motion phase.
Pause durationid PauseDurationtype Kernel, Double datatype (Kernel Catalog).type id kernel, doubleinplace id *no*inherited id *no*
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The duration of the last pause phase.
Parameters
Measure unitid MeasureUnittype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layoutCombo Box:FramesMilliseconds
domain [ 0, 2 )The measure unit for the output durations. It can be frames or milliseconds.
Sampling rateid SamplingRatetype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The sampling rate of the input segmentation signal. This parameter is enabled only ifthe output measure unit is milliseconds.
Continuous outputid ContinuousOutputtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If this parameter is set to false the output is returned only at the end of a motion orpause phase. Otherwise, the last value is continuously returned.
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1.1.17 PixelWeightQuantityOfMotion
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class name PixelWeightQuantityOfMotioncatalog name Gesture Processingcatalog id EywGPclass id pixel weight quantity of motion
Calculate quantity of motion. The block can weight pixels according to parameterweight. — ERROR AND WARNING — - During Initilalization phase. - Matrix and imagemust be the same dimension: if the dimension of the matrix of weight jand the dimensionof the image are different. - Block Internal QOM : The mask or the anchor size are invalid:if the dimensions of median filter are not odd. - During execution phase: - Ipp library info:ippiv81.lib 5.2 5.2.108.410- Ipp Error description : Invalid mask size.
Inputs
input blobid input blobtype Base, Blob 2Dtype id base, blob2d
requiredrequired for initializationrequired for execution
read only/read write read writereferred as inplace *no*referred as inherited *no*
This is the blob extracted from the input image. Actually the block works only with asingle blob.
Outputs
output qomid output qomtype Kernel, Double datatype (Kernel Catalog).type id kernel, doubleinplace id *no*inherited id *no*
Value of qom
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output imageid output imagetype Base, Imagetype id base, imageinplace id *no*inherited id *no*
The image represents differents beetween the first and the last image of a dynamicqueue. The lenght of the queue is expressed by the parameter ’Window lenght’
Parameters
Weightid output qom typetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:EuclideanInverse EuclideanFrom MatrixInverse From MatrixNone
domain [ 0, 5 )The parameter represent the type of weight. Euclidean: the weight of pixels is the
distance from the baricenter. Inverse Euclidean: the weight of pixels is the inverse of thedistance from the baricenter. From Matrix: weights of pixels are stored in the matrix .Inverse From Matrix: weight of pixels are the inverse of the matix. None: There is noweight for each pixel.
WindowLenghtid window lenghttype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 0, +infinity )
The size of a dynamic queue. The queue stores images and the algorithm process thefirst and the last image in the buffer.
Thresholdid thresholdtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The threshold used in the binarization of image.
Resetid resettype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
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Reset the method and clear the queue of images. When reset button is pressed thealgorithmneeds to read ’Window lenght’ images.
Normalization Typeid normalization;type Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:AreaofImageAreaofBoundingRectangleAreaofBlob
domain [ 0, 3 )It specifies if the numeric output is normalized by the area of entire image, by the area
of the bounding rectangle or by the area of the blob.
MedianOnOffid mediantype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Active median filter.
MedianXid median xtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 0, +infinity )
The width of median filter mask used in the method.
MedianYid median ytype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 0, +infinity )
The height of median filter mask used in the method.
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1.1.18 Position Depending Potentials
bitmap
class name Position Depending Potentialscatalog name Gesture Processingcatalog id EywGPclass id PositionDependingPotentialsauthors Gualtiero Volpe
Given a model in which a 2D space is divided in cells, this block computes a 2D potentialfunction depending on the indexes (h, k) of the cells received as input. The kind of potentialfunction can be provided as parameter.
Inputs
Input cellsid InputPositionstype Kernel, Listtype id kernel, list
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
A list of input cells used for computing the potential function. This list contains acollection of 1x2 or 2x1 vectors whose items are the (h, k) indexes of a cell in the space.Usually, this input comes from an Hit Cell Detector and these are the cells occupied by acollection of input points.
Outputs
id OutputPotentialtype Kernel, Double matrix.type id kernel, double-matrixinplace id *no*inherited id *no*
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Parameters
Cells along Xid CellsAlongXtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
The number of cells in which the input space has been divided along the x dimension. Itcorresponds to the number of columns in the output potential matrix. If the block receivesits input from a Hit Cell Detector, this parameter should have the same value than thecorresponding parameter in the Hit Cell Detector. The default value is 10.
Cells along Yid CellsAlongYtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
The number of cells in which the input space has been divided along the y dimension.It corresponds to the number of rows in the output potential matrix. If the block receivesits input from a Hit Cell Detector, this parameter should have the same value than thecorresponding parameter in the Hit Cell Detector. The default value is 10.
Potential typeid PotentialTypetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:Linear increment/decrementPolynomialOccupation ratesGaussianLogarithmic
The kind of potential to be computed. The following options are available at the mo-ment: linear increment /decrement, polynomial, occupation rates, Gaussian, logarithmic.
Use initialization matrixid UseInitMatrixtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Initialization matrix parameter is added as parameter to the blockand displayed. The potential function will be initialized according to the values containedin the matrix provided for the Initialization matrix parameter. Otherwise the potentialfunction is initialized with zeros. The default value is false.
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Resetid Resettype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
Each time a reset command is triggered, the potential function is reinitialized: the newinitial values are those contained in the Initialization matrix or zeros, depending on the Useinitialization matrix parameter.
Increment factorid IncrementFactortype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The increment factor to be applied to the hit cell. For each cell in the input list thisincrement factor is applied. The default value is 1.
Decrement factorid DecrementFactortype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The decrement factor to be applied to missed cells. For each cell which is not in theinput list this decrement factor is applied. The default value is 1.
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1.1.19 Region Depending Potentials
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class name Region Depending Potentialscatalog name Gesture Processingcatalog id EywGPclass id RegionDependingPotentialsauthors Gualtiero Volpe
Given a model in which a 2D space is divided in cells, this block computes a 2D potentialfunction depending on regions defined in such a space and, in particular, on the regionsthat are occupied by points or to which the cells received as input belong. The kind ofpotential function can be provided as parameter.
Inputs
Input listid InputPositionstype Kernel, Listtype id kernel, list
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
A list of either input cells or indexes of hit (occupied) regions. In the former case, thislist contains a collection of 1x2 or 2x1 vectors whose items are the (h, k) indexes of a cellin the space. In the latter, this is a list of integer numbers (region indexes). This inputusually comes from a Hit Cell Detector (and in such a case it is a list of input cells) or froma Hit Region Detector (and in such a case it is list of region indexes). If the input is a listof cells, hit regions indexes are automatically computed.
Outputs
Potential functionid Potentialtype Kernel, Double matrix.type id kernel, double-matrixinplace id *no*inherited id *no*
A matrix representing the computed potential function. The number of items in thismatrix is equal to the number of cells the space is divided in. Therefore, the number of rows
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is equal to the number of cells along y and the number of columns is equal to the numberof cells along x. The output is available only if the Return potential matrix parameter isset to true.
Parameters
Cells along Xid CellsAlongXtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
The number of cells in which the input space has been divided along the x dimension. Itcorresponds to the number of columns in the output potential matrix. If the block receivesits input from a Hit Cell Detector, this parameter should have the same value than thecorresponding parameter in the Hit Cell Detector. The default value is 10.
Cells along Yid CellsAlongYtype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
The number of cells in which the input space has been divided along the y dimension.It corresponds to the number of rows in the output potential matrix. If the block receivesits input from a Hit Cell Detector, this parameter should have the same value than thecorresponding parameter in the Hit Cell Detector. The default value is 10.
Potential typeid PotentialTypetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:Linear increment/decrementLinear occupation ratesExponential occupation rates
The kind of potential to be computed. The following options are available at the mo-ment: linear increment /decrement, polynomial, occupation rates, Gaussian, logarithmic.
Use initialization matrixid UseInitMatrixtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Initialization matrix parameter is added as parameter to the blockand displayed. The potential function will be initialized according to the values containedin the matrix provided for the Initialization matrix parameter. Otherwise the potentialfunction is initialized with zeros. The default value is false.
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Resetid Resettype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
Each time a reset command is triggered, the potential function is reinitialized: the newinitial values are those contained in the Initialization matrix or zeros, depending on the Useinitialization matrix parameter.
Regions maskid Masktype Kernel, Integer matrix.type id kernel, int-matrix
An integer matrix containing the indexes (identifiers) of the regions defined in the space.Items labeled with the same index (integer value) belong to the same region. The rangeis [0, MaxNumOfRegions -1] where MaxNumOfRegions is the maximum number of regionsthat can be defined. Such value is provided through the (Maximum) number of regionsparameter. The size of the mask matrix is automatically computed and it is the samesize of the matrix of the potential function, i.e., the number of rows is the number of cellsalong y and the number of columns is the number of cells along y. In case the input comesfrom a Hit Region Detector, this mask should be the same mask provided to the Hit regiondetector and the number of cells and regions to be set accordingly. The default value is amatrix of zeros.
(Maximum) Number of regionsid NumOfRegionstype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
The maximum number of regions that can be defined. Regions will be labeled withprogressive integer numbers from 0 up to this value minus one. In case the input of theblock comes from a Hit Region Detector, this parameter should be set equal to the size ofThresholds vector in the Hit Region Detector. The default value is 10.
Use initialization values for regionsid UseInitValForRegtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Initialization values for regions parameter is added to the block anddisplayed. The potential function will be initialized according to the values contained in thevector provided for the Initialization values for regions parameter. Otherwise the potentialfunction is initialized with zeros. Since just one way of initializing the potential function isallowed, if the Use initialization matrix parameter is set to true, this one is automaticallyset to false. The default value is false.
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Return potential matrixid OutputPotentialMatrixtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true the Potential function output becomes available and the whole potentialmatrix is returned by the block. The default value is true..
Return hit regionsid OutputHitRegionstype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Hit regions output becomes available and a vector is returned, whereeach item is set to 0 if the corresponding region is missed or to 1 if the corresponding regionis hit. The default value is false.
Return indexes of hit regionsid OutputHitRegionIndexestype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true the Hit regions indexes output becomes available and a list of indexes ofhit regions is returned by the block. The default value is false.
Return region valuesid OutputRegionValuestype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the Region values output becomes available and a vector is returned,where each item is set to the current potential value for the corresponding region. Thedefault value is false.
Increment factorid IncrementFactortype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The increment factor to be applied to hit regions. In case of list of cells as input, foreach cell in the input list this increment factor is applied to the region it belongs to. Thedefault value is 1.
Decrement factorid DecrementFactortype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The decrement factor to be applied to missed regions. In case of list of cells as input,for each cell which is not in the input list this decrement factor is applied to the region itbelongs to. The default value is 1.
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1.1.20 Remove point
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class name Remove pointcatalog name Gesture Processingcatalog id EywGPclass id RemovePointauthors Gualtiero Volpe
This block retrieves the oldest point from the input trajectory and removes it.
Inputs
Input trajectoryid InputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read writereferred as inplace Output pointreferred as inherited *no*
The input trajectory from where the indicated point will be retrieved.
Outputs
Output pointid OutputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatypeinplace id Input trajectoryinherited id *no*
The retrieved output point.
Output pointid OutputPointtype Kernel, Generic datatypetype id kernel, generic datatypeinplace id *no*inherited id *no*
The retrieved output point.
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1.1.21 Set properties
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class name Set propertiescatalog name Gesture Processingcatalog id EywGPclass id SetTrajectoryPropertiesauthors Gualtiero Volpe
This block modifies the properties (label, sampling rate, etc.) of the input trajectory.
Inputs
Input trajectoryid InputTrajectorytype Kernel, Generic datatypetype id kernel, generic datatype
requiredrequired for initializationrequired for execution
read only/read write read writereferred as inplace *no*referred as inherited Output trajectory
The input trajectory whose properties have to be changed.
Outputs
Output trajectoryid OutputTrajectory2type Kernel, Generic datatypetype id kernel, generic datatypeinplace id Input trajectoryinherited id *no*
The output trajectory with the modified properties.
Parameters
Modify labelid ModifyLabeltype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Set this parameter to true if you want to change the trajectory label.
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Modify sizeid ModifySizetype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Set this parameter to true if you want to change the trajectory sizel.
Trajectory labelid Labeltype Kernel, String datatype (Kernel Catalog).type id kernel, string
The label of the trajectory.
Is maximum of points fixed?id IsSizeFixedtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Set this parameter to true if the maximum number of points belonging to the trajectoryis fixed. When such number is reached the oldest points are removed from the trajectory.
Maximum number of pointsid MaxSizetype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 2, +infinity )
The maximum number of points in the generated trajectory. This parameter is availableonly if the maximum number of points is fixed.
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1.1.22 Trajectory from points
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class name Trajectory from pointscatalog name Gesture Processingcatalog id EywGPclass id TrajectoryFromPointsauthors Gualtiero Volpe
This block generates a trajectory conisting of the temporal sequence of the points pro-vided as input.
Inputs
Input 2D point.id InputPointtype Base, Point 2D inttype id base, point 2d int
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input 2D point to be added to the generated trajectory.
Outputs
Output 2D trajectoryid OutputTrajectorytype Gesture Processing, Integer 2D Geometric Trajectorytype id EywGP, IntGeometricTrajectory2Dinplace id *no*inherited id *no*
The generated 2D trajectory
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Parameters
Trajectory typeid TrajectoryTypetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:Geometric Integer 2DGeometric Real 2DGraphic Integer 2DGraphic Real 2DGeometric Integer 3DGeometric Real 3D
domain [ 0, 6 )The type of trajectory to be generated. It may be 2D, 3D or nD, geometric or graphical,
interger or real.
Trajectory labelid Labeltype Kernel, String datatype (Kernel Catalog).type id kernel, string
The label of the generated 2D trajectory.
Sampling rateid SamplingRatetype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The sampling rate in Hz at which the input points are sampled.
Is maximum of points fixed?id IsSizeFixedtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Set this parameter to true if the maximum number of points belonging to the trajectoryis fixed. When such number is reached the oldest points are removed from the trajectory.
Maximum number of pointsid MaxSizetype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 2, +infinity )
The maximum number of points in the generated trajectory. This parameter is availableonly if the maximum number of points is fixed.
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Resetid Resettype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
Reset the generated trajectory by removing all its points.
Colorid Colortype Kernel, RGBColor datatype (Kernel Catalog).type id kernel, rgbcolor
The color of the generated trajectory. The value of this parameter is taken into accountonly if the generated trajectory is a graphic trajectory.
Thicknessid Thicknesstype Kernel, Double datatype (Kernel Catalog).type id kernel, double
The thickness of the generated trajectory. The value of this parameter is taken intoaccount only if the generated trajectory is a graphic trajectory.
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1.2 Datatypes
1.2.1 Double 2D Geometric Contour
class name Double 2D Geometric Contourcatalog name Gesture Processingcatalog id EywGPclass id DoubleGeometricContour
This datatype stores 2D contours and provides information about them.
Supported interfaces
• kernel, trasformation 2d
• EywGP, ContourBase
• EywGP, Contour2DBase
• EywGP, GeometricContour2DBase
• EywGP, ContourAttributes
1.2.2 Double 2D Geometric Trajectory
class name Double 2D Geometric Trajectorycatalog name Gesture Processingcatalog id EywGPclass id DoubleGeometricTrajectory2D
This datatype stores 2D trajectories and provides information about them (e.g., kine-matical features, expressive features).
Supported interfaces
• Base, Transformations2D
• EywGP, TrajectoryBase
• EywGP, Trajectory2DBase
• EywGP, GeometricTrajectory2DBase
• EywGP, TrajectoryAttributes
• EywGP, TrajectoryFeatures
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1.2.3 Double 2D Graphic Contour
class name Double 2D Graphic Contourcatalog name Gesture Processingcatalog id EywGPclass id DoubleGraphicContour
This datatype stores 2D contours and provides information about them.
Supported interfaces
• Base, Transformations2D
• Base, Drawing
• EywGP, ContourBase
• EywGP, Contour2DBase
• EywGP, GraphicContour2DBase
• EywGP, ContourAttributes
1.2.4 Double 2D Graphic Trajectory
class name Double 2D Graphic Trajectorycatalog name Gesture Processingcatalog id EywGPclass id DoubleGraphicTrajectory2D
This datatype stores 2D trajectories and provides information about them (e.g., kine-matical features, expressive features).
Supported interfaces
• Base, Transformations2D
• Base, Drawing
• EywGP, TrajectoryBase
• EywGP, Trajectory2DBase
• EywGP, GraphicTrajectory2DBase
• EywGP, TrajectoryAttributes
• EywGP, TrajectoryFeatures
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1.2.5 Double 3D Geometric Trajectory
class name Double 3D Geometric Trajectorycatalog name Gesture Processingcatalog id EywGPclass id DoubleGeometricTrajectory3D
This datatype stores 3D trajectories and provides information about them (e.g., kine-matical features, expressive features).
Supported interfaces
• kernel, trasformation 3D
• EywGP, TrajectoryBase
• EywGP, Trajectory3DBase
• EywGP, GeometricTrajectory3DBase
• EywGP, TrajectoryAttributes
• EywGP, TrajectoryFeatures
1.2.6 Integer 2D Geometric Contour
class name Integer 2D Geometric Contourcatalog name Gesture Processingcatalog id EywGPclass id IntGeometricContour
This datatype stores 2D contours and provides information about them.
Supported interfaces
• Base, Transformations2D
• EywGP, ContourBase
• EywGP, Contour2DBase
• EywGP, GeometricContour2DBase
• EywGP, ContourAttributes
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1.2.7 Integer 2D Geometric Trajectory
class name Integer 2D Geometric Trajectorycatalog name Gesture Processingcatalog id EywGPclass id IntGeometricTrajectory2D
This datatype stores 2D trajectories and provides information about them (e.g., kine-matical features, expressive features).
Supported interfaces
• Base, Transformations2D
• EywGP, TrajectoryBase
• EywGP, Trajectory2DBase
• EywGP, GeometricTrajectory2DBase
• EywGP, TrajectoryAttributes
• EywGP, TrajectoryFeatures
1.2.8 Integer 2D Graphic Contour
class name Integer 2D Graphic Contourcatalog name Gesture Processingcatalog id EywGPclass id IntGraphicContour
This datatype stores 2D contours and provides information about them.
Supported interfaces
• Base, Transformations2D
• Base, Drawing
• EywGP, ContourBase
• EywGP, Contour2DBase
• EywGP, GraphicContour2DBase
• EywGP, ContourAttributes
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1.2.9 Integer 2D Graphic Trajectory
class name Integer 2D Graphic Trajectorycatalog name Gesture Processingcatalog id EywGPclass id IntGraphicTrajectory2D
This datatype stores 2D trajectories and provides information about them (e.g., kine-matical features, expressive features).
Supported interfaces
• Base, Transformations2D
• Base, Drawing
• EywGP, TrajectoryBase
• EywGP, Trajectory2DBase
• EywGP, GraphicTrajectory2DBase
• EywGP, TrajectoryAttributes
• EywGP, TrajectoryFeatures
1.2.10 Integer 3D Geometric Trajectory
class name Integer 3D Geometric Trajectorycatalog name Gesture Processingcatalog id EywGPclass id IntGeometricTrajectory3D
This datatype stores 3D trajectories and provides information about them (e.g., kine-matical features, expressive features).
Supported interfaces
• Base, Transformations3D
• EywGP, TrajectoryBase
• EywGP, Trajectory3DBase
• EywGP, GeometricTrajectory3DBase
• EywGP, TrajectoryAttributes
• EywGP, TrajectoryFeatures
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1.3 Datatype converters
1.3.1 Geometric To Graphic Trajectory Converter
class name Geometric To Graphic Trajectory Convertercatalog name Gesture Processingcatalog id EywGPclass id IntGeometricToGraphicTrajectory2DConverter
This converter converts a geometric trajectory to a graphic trajectory, i.e., a trajectorythat can be displayed.By default, the output graphic trajectory will be black and will havea thickness of one pixel.
1.3.2 Geometric To Graphic Trajectory Converter
class name Geometric To Graphic Trajectory Convertercatalog name Gesture Processingcatalog id EywGPclass id DoubleGeometricToGraphicTrajectory2DConverter
This converter converts a geometric trajectory to a graphic trajectory, i.e., a trajectorythat can be displayed.By default, the output graphic trajectory will be black and will havea thickness of one pixel.
1.3.3 Graphic To Geometric Trajectory Converter
class name Graphic To Geometric Trajectory Convertercatalog name Gesture Processingcatalog id EywGPclass id IntGraphicToGeometricTrajectory2DConverter
This converter converts a graphic trajectory to a geometric trajectory i.e., it removesgraphic information such as color and thickness.
1.3.4 Graphic To Geometric Trajectory Converter
class name Graphic To Geometric Trajectory Convertercatalog name Gesture Processingcatalog id EywGPclass id DoubleGraphicToGeometricTrajectory2DConverter
This converter converts a graphic trajectory to a geometric trajectory i.e., it removesgraphic information such as color and thickness.
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1.3.5 Trajectory To Dynamic Temporal Data Converter
class name Trajectory To Dynamic Temporal Data Convertercatalog name Gesture Processingcatalog id EywGPclass id DoubleGeomTraj2DToDynTempDataConverter
This converter converts a trajectory to a time series having as many channels as thenumber of componenets of the trajectory points and as many samples as the number ofpoints of the trajectory.
1.3.6 Trajectory To Dynamic Temporal Data Converter
class name Trajectory To Dynamic Temporal Data Convertercatalog name Gesture Processingcatalog id EywGPclass id DoubleGraphicTraj2DToDynTempDataConverter
This converter converts a trajectory to a time series having as many channels as thenumber of componenets of the trajectory points and as many samples as the number ofpoints of the trajectory.
1.3.7 Trajectory To Dynamic Temporal Data Converter
class name Trajectory To Dynamic Temporal Data Convertercatalog name Gesture Processingcatalog id EywGPclass id DoubleGeomTraj3DToDynTempDataConverter
This converter converts a trajectory to a time series having as many channels as thenumber of componenets of the trajectory points and as many samples as the number ofpoints of the trajectory.
1.4 Authors
1.4.1 Gualtiero Volpe
class name Gualtiero Volpecatalog name Gesture Processingcatalog id EywGPclass id gualtiero
Software Engineer mailto:[email protected]
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1.4.2 Paolo Coletta
class name Paolo Colettacatalog name Gesture Processingcatalog id EywGPclass id paolo
1.5 Companies
1.5.1 InfoMus Lab
class name InfoMus Labcatalog name Gesture Processingcatalog id EywGPclass id InfoMus
Laboratory of Musical Informatics http://www.infomus.dist.unige.it news://infomus.dist.unige.itmailto:[email protected]
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Chapter 2
Machine Learning Catalog
2.1 Blocks
2.1.1 LibSVM Save
bitmap
class name LibSVM Savecatalog name Machine Learningcatalog id EywMLclass id LibSVMSaveauthors Gualtiero Volpe
This block allows saving a matrix in the format required by the libsvm tools)
Inputs
Input Matrixid InputMatrixtype Kernel, Double matrix.type id kernel, double-matrix
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input matrix to be saved in LibSVM format
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Parameters
File Nameid FileNametype Kernel, String datatype (Kernel Catalog).type id kernel, string
layout
Filename,MustExist=true,SaveMode=true,OverwritePrompt=true,Filter=”Text files (*.txt)—*.txt—All files (*.*)—*.*——”
Name of the output file that will be formatted in LibSVM style
Save Modeid SaveModetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layoutCombo Box:AppendOverwrite
domain [ 0, 1 ]Specify whether new data should overwrite the older ones or if the new data are ap-
pended after the older ones
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2.1.2 SVM Predict
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class name SVM Predictcatalog name Machine Learningcatalog id EywMLclass id SVMauthors Gualtiero Volpe
This block provides support for performing prediction using Support Vector Machines(SVMs)
Inputs
Input Matrixid InputMatrixtype Kernel, Double matrix.type id kernel, double-matrix
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
Input data to be analysed by the SVM
Outputs
Output Vectorid OutputVectortype Kernel, Double matrix.type id kernel, double-matrixinplace id *no*inherited id *no*
Output from the SVM model
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Parameters
Model File Nameid ModelFileNametype Kernel, String datatype (Kernel Catalog).type id kernel, string
layout
Filename,MustExist=true,SaveMode=false,OverwritePrompt=true,Filter=”Text files (*.txt)—*.txt—All files (*.*)—*.*——”
Name of the file including the SVM model
Refresh modelid RefreshModeltype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
Refresh the SVM model
Show probabilitiesid Probabilitiestype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set, an additional output is generated, providing probabilties values for classes. Notethat the model should be suitably trained in order to provide probabilities values.
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2.1.3 SVM Train
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class name SVM Traincatalog name Machine Learningcatalog id EywMLclass id SVMTrainauthors Gualtiero Volpe
This block provides support for training a Support Vector Machine (SVM)
Inputs
Input Matrixid InputMatrixtype Kernel, Double matrix.type id kernel, double-matrix
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
The input training set
Outputs
Trainedid TrainedFlagtype Kernel, Int datatype (Kernel Catalog).type id kernel, intinplace id *no*inherited id *no*
The block returns a non-zero value if an SVM model has been successfully generated.
Rangesid Rangestype Kernel, Double matrix.type id kernel, double-matrixinplace id *no*inherited id *no*
Ranges of the training set attributes
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Parameters
SVM Typeid SVMTypetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:C-SVCNu-SVCOne-class SVMEpsilon-SVRNu-SVR
domain [ 0, 4 ]Specify the type of SVM
Kernel Typeid KernelTypetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layout
Combo Box:LinearPolynomialRadial Basis FunctionSigmoid
domain [ 0, 3 ]Specify the type of the SVM kernel
Degreeid Degreetype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Degree of the kernel polynome (for polynomial SVMs only)
Gammaid Gammatype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Gamma value for the SVM model
Offsetid Coeff0type Kernel, Double datatype (Kernel Catalog).type id kernel, double
Offset value for the SVM model
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Epsilonid Epsilontype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Stopping criterium
Cache Sizeid CacheSizetype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Cache size in MB
Cid Ctype Kernel, Double datatype (Kernel Catalog).type id kernel, double
C value for the SVM model
Nuid Nutype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Nu value for the SVM model
pid ptype Kernel, Double datatype (Kernel Catalog).type id kernel, double
p value for the SVM model
Shrinkingid Shrinkingtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Use shrinking heuristics
Probabilityid Probabilitytype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
Do probability estimates
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Model File Nameid ModelFileNametype Kernel, String datatype (Kernel Catalog).type id kernel, string
layout
Filename,MustExist=true,SaveMode=true,OverwritePrompt=true,Filter=”Text files (*.txt)—*.txt—All files (*.*)—*.*——”
Name of the file containing the model
Train Modelid TrainModeltype Kernel, Trigger datatype (Kernel Catalog).type id kernel, trigger
Trains the Support Vector Machine
Training Modeid TrainingModetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
layoutCombo Box:IncrementalOne shot
domain [ 0, 1 ]Select whether to incremenatally update the model or to perform a one-shot training.
Enable Maximum Sizeid EnableMaxSizetype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, check for a maximum size of the training set. In case such maximum sizeis reached, training is forced.
Maximum size of training setid MaxSizetype Kernel, Int datatype (Kernel Catalog).type id kernel, int
The maximum allowed size for the training set.
Enable Loggingid EnableLogtype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, enable writing of a log file containing information on the training
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Log File Nameid LogFileNametype Kernel, String datatype (Kernel Catalog).type id kernel, string
layout
Filename,MustExist=true,SaveMode=true,OverwritePrompt=true,Filter=”Text files (*.txt)—*.txt—All files (*.*)—*.*——”
Name of the log file
Scale Valuesid ScaleValuestype Kernel, Bool datatype (Kernel Catalog).type id kernel, bool
If set to true, the block will scale the values in the training set
Lower Boundid LowerBoundtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Lower bound of the rescaled training set
Upper Boundid UpperBoundtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Upper bound of the rescaled training set
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2.1.4 Stabilizer
bitmap
class name Stabilizercatalog name Machine Learningcatalog id EywMLclass id Stabilizerauthors Gualtiero Volpe
This block stabilizes the output of a machine learning classifier.
Inputs
Input valueid InputValuetype Kernel, Double datatype (Kernel Catalog).type id kernel, double
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
Input value to the stabilizer
Outputs
Recognitionid Recognizedtype Kernel, Int datatype (Kernel Catalog).type id kernel, intinplace id *no*inherited id *no*
True if the current value is recognized
Output valueid OutputValuetype Kernel, Double datatype (Kernel Catalog).type id kernel, doubleinplace id *no*inherited id *no*
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Output value from the stabilizer
Parameters
Number of valuesid NValuestype Kernel, Int datatype (Kernel Catalog).type id kernel, intdomain [ 1, +infinity )
Number of previous values the stabilizer takes into account
Thresholdid Thresholdtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Threshold for the stabilizer.
Not recognized valueid NotRecValuetype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Value returned as output when the input is not recognized
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2.1.5 Vector Rescaler
bitmap
class name Vector Rescalercatalog name Machine Learningcatalog id EywMLclass id VectorRescalerauthors Gualtiero Volpe
This block rescales the input vector according to the given ranges.
Inputs
Input Vectorid InputVectortype Kernel, Double matrix.type id kernel, double-matrix
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
Input vector
Input Rangesid InputRangestype Kernel, Double matrix.type id kernel, double-matrix
requiredrequired for initializationrequired for execution
read only/read write read onlyreferred as inplace *no*referred as inherited *no*
Ranges of each item in the input vector
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Outputs
Output Vectorid OutputVectortype Kernel, Double matrix.type id kernel, double-matrixinplace id *no*inherited id *no*
Rescaled vector
Parameters
Lower boundid OutputLowBoundtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Lower bound of the rescaled vector
Upper boundid OutputHighBoundtype Kernel, Double datatype (Kernel Catalog).type id kernel, double
Upper bound of the rescaled vector
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2.2 Datatypes
2.3 Authors
2.3.1 Gualtiero Volpe
class name Gualtiero Volpecatalog name Machine Learningcatalog id EywMLclass id gualtiero
Software Engineer mailto:[email protected]
2.4 Companies
2.4.1 InfoMus Lab
class name InfoMus Labcatalog name Machine Learningcatalog id EywMLclass id InfoMus
InfoMus Lab Laboratory of Musical Informatics http://infomus.dist.unige.it news://infomus.dist.unige.itmailto:[email protected]
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Part III
Appendices
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Appendix A
Release notes
A.1 Notes on EyesWeb XMI Expressive Gesture pro-
cessing Library 5.0.3.0
Released on Xxxx XX, 2009.
• TODO Finally released
• Added block GeneralisedAutoCorrelation
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Appendix B
License
Use of the EyesWeb Gesture Processing Library (hereinafter ’SOFTWARE’) is contingenton your agreement to the following terms:
WARRANTY & USE: DIST - University of Genoa grants you a limited, non-exclusivelicense to use the SOFTWARE free of charge only for educational purposes and researchat universities and government research laboratories. Companies and private research lab-oratories are required to obtain a separate license. For any other (not educational) use,commercial or private, it is also required to obtain a license. DIST - University of Genoamakes no representations about the suitability of this software for any purpose. It is pro-vided ”as is” without express or implied warranty. DIST - University of Genoa is notobligated to provide maintenance or updates for the SOFTWARE.
DISTRIBUTION: universities and government research laboratories may freely dis-tribute the SOFTWARE, in original version, only to other universities and governmentresearch laboratories provided that this copyright and permission notice appear on all copiesand supporting documentation, and that the DIST - University of Genoa copyright noticesare referred in the following ways:
• DIST - University of Genoa’s copyright notice should be included in the documenta-tion, regardless of the media used to supply the documentation;
• The DIST - University of Genoa and EyesWeb Logos have to appear on packages andpromotional material (DIST - University of Genoa makes the logos available on theEyesWeb’s ftp site ftp://ftp.infomus.org;
• In the ’about box’ of the product, in the case that it is not the EyesWeb about box,DIST - University of Genoa and EyesWeb must be cited in the following manner:”EyesWeb is copyright (c) Laboratorio di Infomatica Musicale - DIST - Universityof Genoa (www.infomus.dist.unige.it)”, and the EyesWeb Gesture Processing Librarymust be cited in the following manner: ”The EyesWeb Gesture Processing Libraryis copyright (c) Laboratorio di Infomatica Musicale - DIST - University of Genoa(www.infomus.dist.unige.it)”.
• Any public event or product/applications must be communicated in advance to [email protected].
Distribution to companies, private research laboratories, or any other kind of subjectmust be preliminarly agreed with DIST.
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