关键词: 目标跟踪, 稀疏编码, 稀疏表示, 粒子滤波

Abstract: To deal with the problems in sparse presentation’s application to object tracking, such as the not accurate enough representation of construction error, the wrong update of object templates and so on. This paper proposes a modified sparse coding model. This model doesn’t require the construction error following a particular prior probability density function, and adds an adaptive restraint of the coding coefficient, and this model can acquire better coding vectors for more accurate tracking results. Combined the modified model with the particle filter object tracking algorithm on this basis, a new object tracking method based on the robust sparse coding model is researched and realized. The proposed method encodes every particle’s sample area, uses the sparse coding vector as the observation for the particle, and updates the object templates with different grade to make them more accurate. The experiment results show that the proposed object tracking method can deal well with the corruption like occlusion and illumination variation in object tracking.

Key words: object tracking, sparse coding, sparse representation, particle filter