Abstract:

In order to solve the problem of tracking failure in complex scenes by traditional object tracking algorithms, a new object tracking algorithm based on incremental orthogonal projective non-negative matrix factorization (IOPNMF) with L0 regularization is presented. In the framework of the particle filter, template matrix is obtained on the part-based representation of the tracked object by the IOPNMF algorithm. The candidates in each frame are linearly representated by the template matrix. The representation coefficients are constrained by the L0 regularization while a fast numerical solution is proposed. At the same time, the particle selection mechanism is introduced to speed up the tracking speed. Experimental results show that the proposed algorithm can effectively overcome the influence of occlusion, illumination change, and motion blur, with higher average overlap rate and lower average center point error.