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Shane Tuohy.  In 2008, rear end collisions accounted for almost 25% of all injuries sustained in road traffic accidents on Irish roads [RSA Road Collision.

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Presentation on theme: "Shane Tuohy.  In 2008, rear end collisions accounted for almost 25% of all injuries sustained in road traffic accidents on Irish roads [RSA Road Collision."— Presentation transcript:

1 Shane Tuohy

2  In 2008, rear end collisions accounted for almost 25% of all injuries sustained in road traffic accidents on Irish roads [RSA Road Collision Factbook 2008]  Effective distance determination can go a long way to reducing injuries

3  Mercedes Pre-Safe  Audi Pre-Sense Plus  Toyota Pre-Collision System  All are RADAR systems  Expensive  Cannot detect humans, animals  Susceptible to interference

4  Front facing standard optical camera  Cheap  Many uses  Simple to install

5  Begun by Intel, currently maintained by community, under stewardship of Willow Garage  Extensive library of Computer Vision functions  C, C++, Python, Java  No need to continually ‘reinvent the wheel’

6 Capture Image Process (OpenCV) Feedback To User

7 Capture Image Process (OpenCV) Feedback To User

8 Threshold Image Warp Perspective Determine Distance

9  Remove road surface and highlight objects  Sample road surface in front of vehicle  Remove pixels ±35 of sampled value  Apply binary threshold

10 Threshold Image Warp Perspective Determine Distance

11  Distance in image does not change linearly as vehicle changes position

12  Inverse Perspective Mapping

13  Geometric transform which allows us to remove perspective effect

14 Threshold Image Warp Perspective Determine Distance

15  All road pixels are zero  Analyze area in front of car  Find first non zero pixels  Translate to distance using scaling factor

16  How can we know this ‘scaling factor’?  Need to calibrate for particular camera setup  Can be done once for given environment and parameters  Lay 1m object on road surface  Use chessboard pattern of known size  Roughly calculated for project testing

17 Capture Image Process (OpenCV) Feedback To User

18  Provide graphical feedback to user

19 1. Threshold to remove road surface. Generate transformation matrix 2. Transform image to IPM view 3. Distance determination 4. Graphics overlay 5. Modify algorithm for use on a real time video stream

20  Further work possible  Improve thresholding for different road conditions  Improve performance of IPM algorithm  Automatic calibration implementation  Paper submitted to ISSC 2010, awaiting review  S. Tuohy, D. O Cualain, M. Glavin, E. Jones:“Distance Determination for an Automobile Environment using Inverse Perspective Mapping in OpenCV”  Successful implementation of proposed algorithm

21 Demonstration


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