Spatio-temporal auxiliary particle filtering with l1-Norm- Based Appearance Model Learning for Robust Visual Tracking
In this paper, we propose an efficient and accurate visual tracker equipped with a new particle filtering algorithm and robust subspace learning-based appearance model. The proposed visual tracker avoids drifting problems caused by abrupt motion changes and severe appearance variations that are well...
| Main Authors: | , |
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| Format: | Journal Article |
| Published: |
IEEE
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/56045 |