Abstract
We introduce a fast and robust subspace-based approach to appearance-based object tracking. The core of our approach is based on Fast Robust Correlation (FRC), a recently proposed technique for the robust estimation of large translational displacements. We show how the basic principles of FRC can be naturally extended to formulate a robust version of Principal Component Analysis (PCA) which can be efficiently implemented incrementally and therefore is particularly suitable for robust real-time appearance-based object tracking. Our experimental results demonstrate that the proposed approach outperforms other state-of-the-art holistic appearance-based trackers on several popular video sequences.
Original language | Undefined |
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Title of host publication | IEEE International Conference on Automatic Face & Gesture Recognition and Workshops (FG 2011) |
Place of Publication | USA |
Publisher | IEEE Computer Society |
Pages | 507-513 |
Number of pages | 7 |
ISBN (Print) | 978-1-4244-9140-7 |
DOIs | |
Publication status | Published - Mar 2011 |
Event | 9th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2011 - Santa Barbara, United States Duration: 21 Mar 2011 → 25 Mar 2011 Conference number: 9 |
Publication series
Name | |
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Publisher | IEEE Computer Society |
Conference
Conference | 9th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2011 |
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Abbreviated title | FG |
Country/Territory | United States |
City | Santa Barbara |
Period | 21/03/11 → 25/03/11 |
Keywords
- METIS-285041
- IR-79504
- Video sequences
- Kernel
- Robustness
- HMI-MI: MULTIMODAL INTERACTIONS
- Principal component analysis
- Pixel
- Tracking
- EC Grant Agreement nr.: FP7/231287
- EWI-21349
- Face