Structural signatures for passenger vehicle classification in video

In this paper, we focus on a challenging pattern recognition problem of significant industrial impact: classifying vehicles from their rear videos as observed by a camera mounted on top of a highway with vehicles traveling at high speed. To solve this problem, we present a novel feature called structural signatures. From a rear view video, a structural signature recovers the vehicle side profile information which is crucial in its classification. As a vehicle moves away from a camera, its surfaces deform differently based on their relative orientation to the camera. This information is used to extract the structure of the vehicle which captures the relative orientation of vehicle surfaces and the road surface. We present a complete system which computes the structural signatures and uses them for classification of passenger vehicles into sedans, pickups and Minivans/SUVs in highway videos. We analyze performance of the system on a large dataset.