Fast vehicle detection with probabilistic feature grouping and its application to vehicle tracking

Author

Kim, ZuWhan ; Malik, Jitendra

Author_Institution

Comput. Sci. Div., Univ. of Berkeley, CA, USA

fYear

2003

fDate

13-16 Oct. 2003

Firstpage

524

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.

Keywords

automated highways; computer vision; feature extraction; tracking; video signal processing; ITS; computer vision; fast vehicle detection; intelligent transportation systems; model-based 3-D vehicle detection; probabilistic feature grouping; vehicle description algorithm; vehicle tracking; vehicle trajectory; video data; Application software; Cameras; Computer vision; Detectors; Intelligent transportation systems; Intelligent vehicles; Traffic control; Trajectory; Vehicle detection; Vehicle driving;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on

Conference_Location

Nice, France

Print_ISBN

0-7695-1950-4

Type

conf

DOI

10.1109/ICCV.2003.1238392

Filename

1238392