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Information Technology in Multi-Object Tracking Based on Bilateral Structure Tensor Corner Detection for Mutual Occlusion

For mutual occlusion problem in multi-object tracking process, a novel tracking algorithm based on bilateral structure tensor corner detection is proposed, which can separate the objects correctly when they experience mutual occlusion. Firstly, it gains the information of each object corners. Secondly, when occlusion occurs, it makes use of K nearest neighbor algorithm combining with the nearest algorithm to classify the corners in occlusion region. Finally, the multi-object tracking algorithm is proposed. The experimental results show that the proposed method can separate the objects correctly and track the objects effectively, when they experience mutual occlusion, even the object changes its motion direction after occlusion.