This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Target Tracking by a Single Camera Based on Range-Window Algorithm and Pattern Matching
Technical Paper
2006-01-0140
ISSN: 0148-7191, e-ISSN: 2688-3627
Annotation ability available
Sector:
Language:
English
Abstract
An algorithm, which determines the range of a preceding vehicle by a single image, had been proposed. It uses a “Range-Window Algorithm”. Here in order to realize higher robustness and stability, the pattern matching is incorporated into the algorithm. A single camera system using this algorithm has an advantage over the high cost of stereo cameras, millimeter wave radar and non-robust mechanical scanning in some laser radars. And it also provides lateral position of the vehicle. The algorithm uses several portions of a captured image, namely windows. Each window is corresponding to a predetermined range and has the fixed physical width and height. In each window, the size and position of objects in the image are estimated through the ratio between the widths of the objects and the window, and a score is given to each object. The object having the highest score is determined as the best object. The range of the window corresponding to the best object becomes an estimated range. The pattern matching helps this algorithm when the camera image is influenced by a shadow. Since this matching adopts a warped template, it can estimate the range. This algorithm was applied to more than 4,500 real road images. It showed the range accuracy of about +/- 1 [m] and 94% detection rate for a motorcycle, sedan, minivan, truck and bus on rural, urban and city roads. And the incorporation of the pattern matching has improved the detection rate up to 97%. The present maximum range is 50 [m]. This algorithm is effective for the short range application like “Low speed follower”.
Recommended Content
Authors
Topic
Citation
Miyahara, S., Sielagoski, J., Koulinitch, A., and Ibrahim, F., "Target Tracking by a Single Camera Based on Range-Window Algorithm and Pattern Matching," SAE Technical Paper 2006-01-0140, 2006, https://doi.org/10.4271/2006-01-0140.Also In
SAE 2006 Transactions Journal of Passenger Cars: Electronic and Electrical Systems
Number: V115-7; Published: 2007-03-30
Number: V115-7; Published: 2007-03-30
References
- Jones W. D. “Keeping Cars from Crashing” IEEE Spectrum 40 45 Sept. 2001
- Miyahara S. “New Algorithm for the Range Estimation by a Single Frames of a Single Camera” 2005 SAE World Congress, 2005-01-1475 April 2005
- Hanawa K. Sogawa Y. “Development of Stereo Image Recognition System for ADA” Proceedings IEEE Intelligent Vehicles Symposium 2001 177 182 2001
- Kato T. Ninomiya Y. Masaki I. “An Obstacle Detection Method by Fusion of Radar and Motion Stereo” IEEE Trans. Intelligent Transportation Systems 3-3 182 188 Sept. 2002
- Beauvais M. Lakshmanan S. “CLARK: a heterogeneous sensor fusion method for finding lanes and obstacles” Image and Vision Computing 18 397 413 2000
- Higashida H. Nakamura R. Hitotsuya M. Honda K. F. Shima N. “Fusion Sensor for an Assist System for Low Speed in Traffic Congestion Using Millimeter-Wave and an Image Recognition sensor” SAE2001, 2001-01-0800 2001
- Shimomura N. Fujimoto K. Oki T. Muro H. “An Algorithm for Distinguishing the Types of Objects on the Road Using Laser Radar and Vision” IEEE Trans. Intelligent Transportation Systems 3-3 189 195 Sept. 2002
- Stein G. P. Mano O. Shashua A. “Vision-based ACC with a Single Camera: Bounds on the Range and Range Rate Accuracy” IEEE Intelligent Vehicles Symposium (IV2003) June 2003 Columbus, OH
- Dagan E. Mano O. Stein G. P. Shashua A. “Forward Collision Warning with a Single Camera” IEEE Intelligent Vehicle Symposium (IV2004) Parma, Italy Jun. 2004