Model-based car tracking through the integration of search and estimation
Hichem Sahli, Mark J. W. Mertens, Jan P. Cornelis · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
In this work we address the problem of detecting and tracking moving vehicles in image sequences on highway scenes recorded by a moving camera. The proposed method uses a simple parameterized vehicle shape (object-model) and vehicle motion model for an intra-frame matching and a recursive estimation of position, orientation, velocity and shape parameters of the tracked vehicle. In our approach the vehicle detection/identification (matching) is tackled in an optimization framework, implemented as a hypothesis generation and testing method, in which the current set of hypotheses (vehicle shape) are evaluated and modified until a maximum cost instantiation is found. The estimation of the vehicle position, orientation and velocity is based on a ground plane motion constraint and a Kalman Filtering approach. Results on real world highway scenes are presented and open problems are discussed.