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

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.