Fast vehicle detection with probabilistic feature grouping and its application to vehicle tracking
Kim, Z.
Malik, J.
Comput. Sci. Div., Univ. of Berkeley, CA, USA;
This paper appears in: Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Publication Date: 13-16 Oct. 2003
On page(s): 524-531 vol.1
Location: Nice, France,
ISBN: 0-7695-1950-4
INSPEC Accession Number: 8301657
Digital Object Identifier: 10.1109/ICCV.2003.1238392
Current Version Published: 2008-04-03
Abstract
Generating vehicle trajectories from video data is an important application of ITS (intelligent transportation systems). We introduce a new tracking approach which uses model-based 3-D vehicle detection and description algorithm. Our vehicle detection and description algorithm is based on a probabilistic line feature grouping, and it is faster (by up to an order of magnitude) and more flexible than previous image-based algorithms. We present the system implementation and the vehicle detection and tracking results.
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