ruwan egoda gamage , abhishek joshi, jiang yu zheng , mihran tuceryan

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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

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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 Presentation

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Page 1: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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

Page 2: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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.

Page 3: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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

Page 4: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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

 

Page 5: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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

Page 6: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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.

Page 7: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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.

Page 8: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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.

Page 9: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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

Page 10: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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

Page 11: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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

Page 12: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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SOME EXAMPLE SCANS

Depth scan: depth color coded

2D color image acquired registered with depth image.

Page 13: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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SHOE SCAN

3D scan (pseudo-color) Color-texture image

Page 14: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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SCAN OF A SHOEDetecting fine details:Shoe and desired features provided by expert

Features detected in our scan

Page 15: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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LONG TIRE IMPRESSION RESULTS

z range: 307.1mm-259.2mm. Brighter points are closer to camera

Page 16: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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

Page 17: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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SOFTWARE USER INTERFACEWe built a software interface to perform metric measurements on the acquired image

Page 18: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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INTERFACES TO OPERATE THE DEVICEButton InterfaceProgrammed the motor to perform following

• Stop• Homing • Short Run • Long Run

Page 19: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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TABLET BASED WIRELESS INTERFACEBluetooth wireless Interface via tablet:

• more configuration options possible.

Page 20: Ruwan Egoda Gamage ,  Abhishek  Joshi, Jiang Yu  Zheng ,  Mihran Tuceryan

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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.