CHEN Can1,2, CHEH Zhaojiong1,2, GU Yang1,2, YE Dongyi1,2
1.College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350116; 2.Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education, Fuzhou University, Fuzhou 350116
Abstract:When partition-based correlation filtering tracking algorithm is applied to deal with scale changes and target occlusion problems, the estimation of local sub-block state tracking and the relationship between local sub-block and scale change are inaccurate.To address this issue, a scale-aware partition-based cooperative correlation filter tracking algorithm is proposed. A method of local sub-block occlusion discrimination based on time-sequence smooth constraint is adopted, and the scoring strategy of the existing algorithm is improved. A cooperative motion strategy for sub-blocks is then designed to make the occluded or the deformed sub-blocks follow the normal ones to their due positions. And the ratio between target scale and distributed location of sub-blocks aggregation and dispersion is discovered to perceive target scale changes and estimate sizes. Experiments indicate that the proposed algorithm achieves better performance.
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