Object Tracking Using Voting Algorithms

Object tracking based on voting mechanisms, specifically implementing a multi-object tracking algorithm through second-order nonlinear voting. This approach matches object positions across frames by comparing feature similarities between previous and current frames using a voting strategy. The algorithm incorporates feature monitoring to address occlusion and fragmentation issues while enabling real-time feature updates. Experimental results demonstrate strong robustness against noise, shadows, occlusion, and object splits.