Over-Height Vehicle Detection in Low Headroom Roads Using Digital Video Processing

In this paper we present a new method for over-height vehicle detection in low headroom streets and highways using digital video possessing. The accuracy and the lower price comparing to present detectors like laser radars and the capability of providing extra information like speed and height measurement make this method more reliable and efficient. In this algorithm the features are selected and tracked using KLT algorithm. A blob extraction algorithm is also applied using background estimation and subtraction. Then the world coordinates of features that are inside the blobs are estimated using a noble calibration method. As, the heights of the features are calculated, we apply a threshold to select overheight features and eliminate others. The over-height features are segmented using some association criteria and grouped using an undirected graph. Then they are tracked through sequential frames. The obtained groups refer to over-height vehicles in a scene.




References:
[1] CSE Intelligent Transport Systems, online:
http://www.cse-global.com/solutions/its_product.asp
[2] L. A. Klein, M. K. Mills and D. R. Gibson, Traffic Detector Handbook.
vol. 1, Federal Highway Administration, 2006.
[3] S. Gupte, O. Masoud, R. F. K. Martin, and N. P. Papanikolopoulos,
"Detection and classification of vehicles", IEEE Trans. on Intelligent
Transportation Systems, vol. 3, pp. 37-47, Mar. 2002.
[4] D. Magee, "Tracking multiple vehicles using foreground, background
and motion models", Image and Vision Computing, vol 22(2), pp. 143-
155, 2004.
[5] M. Haag and H. Nagel, "Combination of edge element and optical flow
estimate for 3D-model-based vehicle tracking in traffic image
sequences", International Journal of Computer Vision, pp. 295-319,
1999.
[6] N. Kanhere, S. Pundlik and S. Birchfield, "Vehicle segmentation and
tracking from a low-angle off-axis camera", in IEEE Conference on
ComputerVision and Pattern Recognition, pp. 1152-1157, 2005.
[7] E. Trucco and A. Verri, Introductory Techniques for 3-D Computer
Vision. Prentice Hall, 1998, pp. 39.
[8] X. Fu, Z. Wang, D. Liang and J. Jiang, " The Extraction of Moving
Object in Real-Time Web-Based Video Sequence", in The 8th
International Conference on Digital Object Identifier, Vol. 1, pp. 187-
190, 2004.
[9] C. Tomasi and T. Kanade, "Detection and tracking of point features,"
Carnegie Mellon University , Technical Report CMU-CS-91-132, 1991.