Cooperative Object Tracking Algorithm Based on Epipolar Geometry Constrained Particle Filter

In order to improve the performance of particle filter object tracking algorithm based on two-view geometry, cooperative object tracking algorithm based on epipolar geometry constrained particle filter(EGCPF) is proposed. Using the epipolar geometry constraint, on one hand, the object detecting region is restricted during the tracking process to reduce the search space; on the other hand, the state transfer model of particle filtering algorithm is modified to decrease the total number of particles required for each camera with object in the overlap region. Finally, the frame rate, center error and coverage is introduced to measure the performance of the proposed algorithm. The experimental results showed that EGCPF algorithm met requirement in real-time performance, and the accuracy was improved obviously compared with the classical particle filter based object tracking algorithm.