Multi-scale patch-based sparse appearance model for robust object tracking

Chengjun Xie; Jieqing Tan; Peng Chen; Jie Zhang; Lei He

doi:10.1007/s00138-014-0632-3

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Multi-scale patch-based sparse appearance model for robust object tracking

Chengjun Xie Jieqing Tan Peng Chen Jie Zhang Lei He

Year: 2014 Journal: Machine Vision and Applications Vol: 25 (7)Pages: 1859-1876 Publisher: Springer Science+Business Media

DOI: 10.1007/s00138-014-0632-3

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Keywords:

Computer science Artificial intelligence Computer vision Similarity (geometry) Scale (ratio) Video tracking Tracking (education) Sparse approximation Eye tracking Object (grammar) Pattern recognition (psychology) Particle filter Active appearance model Frame (networking) Representation (politics) Ground truth Filter (signal processing) Image (mathematics)

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Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Vision and Imaging

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Face recognition and analysis

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Multi-scale patch-based sparse appearance model for robust object tracking

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