Video Image Object Tracking Algorithm based on Improved Principal Component Analysis

Journal of Multimedia

关键词: Object Appearance Description;    Subspace Updating Algorithm;    Incremental Learning;    Sparse-Representation;    Object Tracking;   

Others  :  1017224
DOI  :  10.4304/jmm.9.5.722-728

【 摘 要 】

Since the existing object tracking algorithms are very difficult to adapt the object appearance changes caused by illumination changes, large pose variations, and partial or full occlusions, an object tracking algorithm based on two-dimensional principal component analysis (2DPCA) and sparse-representation is proposed in this paper. The tracking algorithm adopts 2DPCA and sparse-representation to establish object appearance model. In order to reduce dimension of object template, incremental subspace updating algorithm is introduced to online update the object template, reduce the requirement of memory space and enhance the precision of object appearance description. Experimental results show the proposed algorithm is robust for image illumination variance and object partial occlusion.

【 授权许可】

   
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