Lie-struck: Affine tracking on lie groups using structured SVM

Proceedings - 2015 IEEE Winter Conference on Applications of Computer Vision, WACV 2015

Volumn , Issue , 2015, Pages 63-70

  Zhu, Gao ^a   Porikli, Fatih ^a,b   Ming, Yansheng ^a   Li, Hongdong ^a,c  

^a AUSTRALIAN NATIONAL UNIVERSITY   (Australia)

^b CSIRO   (Australia)

^c AUSTRALIAN CENTRE FOR ROBOTIC VISION   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

DEGREES OF FREEDOM (MECHANICS); LIE GROUPS; LINEAR TRANSFORMATIONS; MODEL STRUCTURES;

AFFINE TRANSFORMATIONS; APPEARANCE MODELING; COMPUTATIONAL LOADS; OBJECT TRANSFORMATION; PREDICTION FUNCTION; SIX DEGREES OF FREEDOM; TRACKING BY DETECTIONS; TRACKING PERFORMANCE;

MOTION TRACKING;

EID: 84925382227     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WACV.2015.16     Document Type: Conference Paper

References (35)

1. VOT2014 Challenge. http://www.votchallenge. net/vot2 014/index.html.
2. T. Albrecht, M. Luthi, and T. Vetter. A statistical deformation prior for non-rigid image and shape registration. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
3. S. Avidan. Support vector tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(8):1064-1072, 2004.
4. B. Babenko, M.-H. Yang, and S. Belongie. Visual tracking with online multiple instance learning. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009.
5. S. Baker and I. Matthews. Equivalence and efficiency of image alignment algorithms. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2001.
6. S. Baker and I. Matthews. Lucas-Kanade 20 years on: A unifying framework. International Journal of Computer Vision, 56(3):221-255, 2004.
7. E. Bayro-Corrochano and J. Ortegon-Aguilar. Lie algebra template tracking. In International Conference on Pattern Recognition (ICPR), 2004.
8. M. B. Blaschko and C. H. Lampert. Learning to localize objects with structured output regression. In European Conference on Computer Vision (ECCV), 2008.
9. A. Bordes, L. Bottou, P. Gallinari, and J. Weston. Solving multiclass support vector machines with LaRank. In International Conference on Machine Learning (ICML), 2007.
10. A. Bordes, N. Usunier, and L. Bottou. Sequence labelling SVMs trained in one pass. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD),2008.
11. Y. Boykov and D. Huttenlocher. Adaptive bayesian recognition in tracking rigid objects. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2000.
12. T. Cootes, G. Edwards, and C. Taylor. Active appearance models. In European Conference on Computer Vision (ECCV), 1998.
13. T. Drummond and R. Cipolla. Application of Lie algebras to visual servoing. International Journal on Computer Vision, 37:21-11, 2000.
14. H. Grabner, M. Grabner, and H. Bischof. Real-time tracking via on-line boosting. In British Machine Vision Conference (BMVC),2006.
15. G. Guennebaud, B. Jacob, et al. Eigen v3. http://eigen.tuxfamily.org, 2010.
16. S. Hare, A. Saffari, and P. H. S. Torr. Struck: Structured output tracking with kernels. In IEEE International Conference on Computer Vision (ICCV), 2011.
17. W. He, T. Yamashita, H. Lu, and S. Lao. SURF tracking. In International Conference on Computer Vision (ICCV), 2009.
18. M. Isard and I. Blake. Condensation-conditional density propagation for visual tracking. International Journal on Computer Vision, 29:5-28, 1998.
19. J. Kwon, K. M. Lee, and F. Park. Visual tracking via geometric particle filtering on the affine group with optimal im-portance functions. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009.
20. B. D. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. In International Joint Conference on Artificial Intelligence (IJCAI), 1981.
21. H. Masnadi-Shirazi, V. Mahadevan, and N. Vasconcelos. On the design of robust classifiers for computer vision. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010.
22. I. Matthews and S. Baker. Active appearance models revisited. International Journal of Computer Vision, 60:135-164, 2004.
23. M. Ozuysal, P. Fua, and V. Lepetit. Fast keypoint recognition in ten lines of code. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007.
24. J. C. Platt. Advances in kernel methods. chapter Fast Training of Support Vector Machines Using Sequential Minimal Optimization, pages 185-208. MITPress, 1999.
25. D. A. Ross, J. Lim, R.-S. Lin, and M.-H. Yang. Incremental learning for robust visual tracking. International Journal on Computer Vision, 77(1-3):125-141, 2008.
26. W. Rossmann. Lie groups: A introduction through linear groups. Oxford University Press, 2002.
27. A. Saffari, M. Godec, T. Pock, C. Leistner, and H. Bischof. Online multi-class LPBoost. In IEEE Computer Vision and Pattern Recognition (CVPR), 2010.
28. A. Saffari, C. Leistner, M. Godec, and H. Bischof. Robust multi-view boosting with priors. In European Conference on Computer Vision Conference on Computer Vision (ECCV), 2010.
29. I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Al-tun. Large margin methods for structured and interdependent output variables. Journal of Machine Learning Research, 6:1453-1484, 2005.
30. O. Tuzel, F. Porikli, and P. Meer. Learning on Lie groups for invariant detection and tracking. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.
31. T. Vetter and T. Poggio. Linear object classes and image synthesis from a single example image. IEEE Transaction on Pattern Analysis and Machine Intelligence, 19:733-742, 1997.
32. D. Wagner, T. Langlotz, and D. Schmalstieg. Robust and unobtrusive marker tracking on mobile phones. In ACM International Symposium on Mixed and Augmented Reality (IS-MAR), 2008.
33. Z. Wang, K. Crammer, and S. Vucetic. Multi-class Pegasos on a budget. In International Conference on Machine Learning (ICML), 2010.
34. J. Xing, J. Gao, B. Li, W. Hu, and S. Yan. Robust object tracking with online multi-lifespan dictionary learning. In IEEE International Conference on Computer Vision (ICCV), 2013.
35. 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), 2012.