ruwan egoda gamage , abhishek joshi, jiang yu zheng , mihran tuceryan
DESCRIPTION
A High Resolution 3D Tire and Footprint Impression Acquisition Device for Forensics Applications. Ruwan Egoda Gamage , Abhishek Joshi, Jiang Yu Zheng , Mihran Tuceryan Computer Science Department, IUPUI. Acknowledgement. - PowerPoint PPT PresentationTRANSCRIPT
A HIGH RESOLUTION 3D TIRE AND FOOTPRINT IMPRESSION ACQUISITION DEVICE FOR FORENSICS APPLICATIONS
RUWAN EGODA GAMAGE, ABHISHEK JOSHI,JIANG YU ZHENG, MIHRAN TUCERYANCOMPUTER SCIENCE DEPARTMENT, IUPUI
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ACKNOWLEDGEMENTThis project was supported by Award No. 2010-DN-BX-K145, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this exhibition are those of the author(s) and do not necessarily reflect those of the Department of Justice.Also thanks to Mr. Alan Kainuma for providing the test shoe.
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OBJECTIVES• Acquire 3D depth images of tire and shoeprint
impressions in a non-destructive way• Simultaneously obtain a high resolution
registered 2D color image• Acquire long tire impressions in one scan (no
stitching of multiple images necessary)• Portable design and easy to use for outdoor
capture• Also scan shoes and tires themselves for
matching purposes
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BASIC DESIGN OF THE HARDWARE
• Camera assembly moves at a precise and fixed speed along the rail.
• The slower it moves, the better resolution along rail direction (slowest speed: 1.3 mm/sec at 30 fps).
Control box
Power supply
HD camcorder
Red stripe laser light
Green stripe laser light
Actuator motion directionSpeed: 1-3mm/sec
Actuator rail: 1.75m long
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WHY TWO LASERS?To be able to handle occlusions.
Green light occluded in this region,but red light visible.
Occluding surface
Scanner motion
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BASIC DESIGN OF DEPTH EXTRACTION
One line per video frame per laser One for red, one for green laser Depth variations on the surface
result in deformations in the laser line.o The amount of deformation is
used to estimate the depth values.
Depth values are calculated along the detected laser line.
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IMAGING GEOMETRYIn order to calculate depth from laser deformation in the image, we need to know the configuration of the camera and laser lights with respect to each other.This can be estimated via a calibration procedure.We do not want to perform calibration ahead of time, because the configuration can change during transportation or setup of the device.
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DEVICE CALIBRATIONOur device has a calibration procedure that is integrated with the scan. Put calibration object (with known dimensions) into the scene and scan.
• The calibration is done as part of the post-processing.• Don’t worry about imaging geometry getting messed up
during transportation and set-up.
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CALIBRATIONIdeally the camera should be set orthogonal to the rail, but this is not realistic.
• We correct camera’s roll and tilt as part of calibration.
Coordinate systems defined for calibration:
X’
Y’
Z’
X
Y
Z
x
y
z
rail
X’Y’
Z’
XY
Z
xy
z
Camera coordinate system
After correcting roll and tilt
Rail coordinate system with respect to which all depth values are computed
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CALIBRATIONPlace an L-shaped calibration object with known dimensions in the scene From the recorded video, select two images with lasers on the calibration objectBecause of the linear motion along the rail, motion vectors of corner points in the FOV have a vanishing point p(x0, y0).Compute vanishing point using corners of the calibration object to estimate tilt and roll of camera
• This is used to correct for tilt and roll of the camera.
A1B1
C1
D1
E1
F1
L1 L3L2
p(x0,y0)
A2B2 C2
D2E2F2
Calibration object
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CALIBRATIONLaser on L-shaped object
• Baseline length between two frames is known from the speed of rail motion and frame numbers (30 fps capture)
• 3D positions of corner points on a calibration object are captured using a user interface
Camera-laser relation• Find the 3D laser lines on the
calibration object to estimate the normal vector of the laser plane
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SOME EXAMPLE SCANS
Depth scan: depth color coded
2D color image acquired registered with depth image.
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SHOE SCAN
3D scan (pseudo-color) Color-texture image
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SCAN OF A SHOEDetecting fine details:Shoe and desired features provided by expert
Features detected in our scan
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LONG TIRE IMPRESSION RESULTS
z range: 307.1mm-259.2mm. Brighter points are closer to camera
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ACCURACYWe did a systematic testing of the accuracy achieved in scanned images by designing and building a test object.
Accuracy Summary• Horizontal resolution
0.23mm (perpendicular to rail motion)
• Rail direction resolution ≥0.043mm
• Depth resolution ~0.5mm
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SOFTWARE USER INTERFACEWe built a software interface to perform metric measurements on the acquired image
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INTERFACES TO OPERATE THE DEVICEButton InterfaceProgrammed the motor to perform following
• Stop• Homing • Short Run • Long Run
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TABLET BASED WIRELESS INTERFACEBluetooth wireless Interface via tablet:
• more configuration options possible.
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CONCLUSION• Achieved 0.5mm depth accuracy.• The prototype device is promising• Accuracy can be improved by improving the
subcomponents of the system or by improving the algorithms.
• Shoes and tires themselves can be scanned to be used for automated matching against a database or for computing degree of match results.