Depth assisted visual tracking

We propose a depth assisted video object tracking algorithm that utilizes stereo vision technique to detect and handle various types of occlusions. The foreground objects are detected by using a depth and motion-based segmentation method. The occlusion detection error caused by inaccurate motion vectors is avoided by combining the depth segmentation results with the previous occlusion status of each track. According to the occlusion analysis results, different object correspondence algorithms are employed to track objects under various occlusions. The proposed severe and complete occlusion handling method does not have assumptions of constant movement and limited maximum duration. Experimental results demonstrate that the proposed system can accurately track multiple objects in complex scene under different occlusions.