  To overcome the problem of occlusion in visual tracking, this paper proposes
an occlusion-aware tracking algorithm. The proposed algorithm divides the
object into discrete image patches according to the pixel distribution of the
object by means of clustering. To avoid the drifting of the tracker to false
targets, the proposed algorithm extracts the dominant features, such as color
histogram or histogram of oriented gradient orientation, from these image
patches, and uses them as cues for tracking. To enhance the robustness of the
tracker, the proposed algorithm employs an implicit spatial structure between
these patches as another cue for tracking; Afterwards, the proposed algorithm
incorporates these components into the particle filter framework, which results
in a robust and precise tracker. Experimental results on color image sequences
with different resolutions show that the proposed tracker outperforms the
comparison algorithms on handling occlusion in visual tracking.
