Object tracking via non-Euclidean geometry: A Grassmann approach

2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014

Volumn , Issue , 2014, Pages 901-908

  Shirazi, Sareh ^a   Harandi, Mehrtash T ^a   Lovell, Brian C ^a   Sanderson, Conrad ^a  

^a CSIRO   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

VIDEO STREAMING;

ILLUMINATION VARIATION; MARKOV CHAIN MONTE-CARLO; NON-EUCLIDEAN GEOMETRY; PARTICLE FILTERING; QUANTITATIVE EVALUATION; STATE-OF-THE-ART METHODS; TRACKING APPROACHES; VISUAL TRACKING SYSTEMS;

FACE RECOGNITION;

EID: 84904659944     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WACV.2014.6836008     Document Type: Conference Paper

References (26)

1. A. Adam, E. Rivlin, and I. Shimshoni. Robust fragments-based tracking using the integral histogram. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 798-805, 2006
2. M. Arulampalam, S. Maskell, N. Gordon, and T. Clapp. A tutorial on particle filters for on-line nonlinear/non-gaussian bayesian tracking. IEEE Trans. Signal Processing, 50(2):174-188, 2002
3. B. Babenko, M. Yang, and S. Belongie. Visual tracking with online multiple instance learning. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 983-990, 2009
4. B. Babenko, M. Yang, and S. Belongie. Robust object tracking with online multiple instance learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(8):1619-1632, 2011
5. R. Basri, T. Hassner, and L. Zelnik-Manor. Approximate nearest subspace search. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(2):266-278, 2011
6. S. Birchfield. Elliptical head tracking using intensity gradients and color histograms. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 232-237, 1998
7. A. Edelman, T. Arias, and S. Smith. The geometry of algorithms with orthogonality constraints. SIAM Journal on Matrix Analysis and Applications, 20(2):303-353, 1998
8. H. Grabner, M. Grabner, and H. Bischof. Real-Time tracking via on-line boosting. In British Machine Vision Conference, volume 1, pages 47-56, 2006
9. J. Hamm and D. Lee. Extended Grassmann kernels for subspacebased learning. In Advances in Neural Information Processing Systems (NIPS), pages 601-608, 2009
10. M. Harandi, C. Sanderson, C. Shen, and B. C. Lovell. Dictionary learning and sparse coding on Grassmann manifolds: An extrinsic solution. In Int. Conference on Computer Vision (ICCV), 2013
11. M. Harandi, C. Sanderson, S. Shirazi, and B. C. Lovell. Graph embedding discriminant analysis on Grassmannian manifolds for improved image set matching. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 2705-2712, 2011
12. M. Harandi, C. Sanderson, S. Shirazi, and B. C. Lovell. Kernel analysis on Grassmann manifolds for action recognition. Pattern Recognition Letters, 34(15):1906-1915, 2013
13. J. Ho, K. Lee, M. Yang, and D. Kriegman. Visual tracking using learned linear subspaces. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), volume 1, pages 782-789, 2004
14. M. Isard and A. Blake. Contour tracking by stochastic propagation of conditional density. European Conference on Computer Vision (ECCV), pages 343-356, 1996
15. Z. Kalal, K. Mikolajczyk, and J. Matas. Tracking-learning-detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(7):1409-1422, 2012
16. T. Kim, J. Kittler, and R. Cipolla. Discriminative learning and recognition of image set classes using canonical correlations. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29(6):1005-1018, 2007
17. J. Kittler, M. Hatef, R. Duin, and J. Matas. On combining classifiers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(3):226-239, 1998
18. X. Li, A. Dick, C. Shen, A. Van Den Hengel, and H. Wang. Incremental learning of 3D-DCT compact representations for robust visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(4):863-881, 2013
19. D. Ross, J. Lim, R. Lin, and M. Yang. Incremental learning for robust visual tracking. Int. Journal of Computer Vision (IJCV), 77(1):125-141, 2008
20. C. Sanderson, M. Harandi, Y. Wong, and B. C. Lovell. Combined learning of salient local descriptors and distance metrics for image set face verification. In IEEE International Conference on Advanced Video and Signal-Based Surveillance (AVSS), pages 294-299, 2012
21. S. Shirazi, M. Harandi, C. Sanderson, A. Alavi, and B. C. Lovell. Clustering on Grassmann manifolds via kernel embedding with application to action analysis. In Int. Conference on Image Processing (ICIP), pages 781-784, 2012
22. P. Turaga, A. Veeraraghavan, A. Srivastava, and R. Chellappa. Statistical computations on Grassmann and Stiefel manifolds for image and video-based recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(11):2273-2286, 2011
23. U. Von Luxburg. A tutorial on spectral clustering. Statistics and Computing, 17(4):395-416, 2007
24. S. Wang, H. Lu, F. Yang, and M.-H. Yang. Superpixel tracking. In Int. Conference on Computer Vision (ICCV), pages 1323-1330, 2011
25. T. Wang, A. Backhouse, and I. Gu. Online subspace learning on Grassmann manifold for moving object tracking in video. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 969-972, 2008
26. W. Zhong, H. Lu, and M.-H. Yang. Robust object tracking via sparsity-based collaborative model. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1838-1845, 2012.