Online learning and detection with part-based, circulant structure

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2014, Pages 4229-4233

  Akin, Osman ^a   Mikolajczyk, Krystian ^b  

^a HACETTEPE UNIVERSITY   (Turkey)

^b UNIVERSITY OF SURREY   (United Kingdom)

Author keywords

Circulant structure kernel; Part based tracking; Tracking by detection

Indexed keywords

FREQUENCY SHIFT KEYING; PATTERN RECOGNITION;

CIRCULANTS; DETECTION FRAMEWORK; LONG-TERM TRACKING; ONLINE LEARNING; PART-BASED TRACKING; PARTIAL OCCLUSIONS; STATE OF THE ART; TRACKING BY DETECTIONS;

E-LEARNING;

EID: 84919940861     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2014.725     Document Type: Conference Paper

References (21)

1. B. Babenko, M.-H. Yang, and S. Belongie, "Visual tracking with online multiple instance learning," in CVPR, IEEE, 2009.
2. Z. Kalal, K. Mikolajczyk, and J. Matas, "Tracking-learning-detection," IEEE TPAMI, vol. 34, no. 7, pp. 1409-1422, 2012.
3. S. Hare, A. Saffari, and P. H. Torr, "Struck: Structured output tracking with kernels," in ICCV, IEEE, 2011.
4. Y. Wu, J. Lim, and M.-H. Yang, "Online object tracking: A benchmark," in CVPR, IEEE, 2013.
5. H. Yang, L. Shao, F. Zheng, L. Wang, and Z. Song, "Recent advances and trends in visual tracking: A review," Neurocomputing, vol. 74, no. 18, pp. 3823-3831, 2011.
6. H. Grabner, M. Grabner, and H. Bischof, "Real-time tracking via online boosting.," in BMVC, 2006.
7. M. Tian, W. Zhang, and F. Liu, "On-line ensemble svm for robust object tracking," in ACCV, Springer, 2007.
8. M. Godec, C. Leistner, A. Saffari, and H. Bischof, "On-line random naive bayes for tracking," in ICPR, IEEE, 2010.
9. H. Grabner, C. Leistner, and H. Bischof, "Semi-supervised on-line boosting for robust tracking," in ECCV, Springer, 2008.
10. X. Jia, H. Lu, and M.-H. Yang, "Visual tracking via adaptive structural local sparse appearance model," in CVPR, IEEE, 2012.
11. W. Zhong, H. Lu, and M.-H. Yang, "Robust object tracking via sparsitybased collaborative model," in CVPR, IEEE, 2012.
12. K. Zhang, L. Zhang, and M.-H. Yang, "Real-time compressive tracking," in ECCV, Springer, 2012.
13. S. Wang, H. Lu, F. Yang, and M.-H. Yang, "Superpixel tracking," in ICCV, IEEE, 2011.
14. A. Adam, E. Rivlin, and I. Shimshoni, "Robust fragments-based tracking using the integral histogram," in CVPR, IEEE, 2006.
15. E. Erdem, S. Dubuisson, and I. Bloch, "Fragments based tracking with adaptive cue integration," CVIU, vol. 116, no. 7, pp. 827-841, 2012.
16. J. F. Henriques, R. Caseiro, P. Martins, and J. Batista, "Exploiting the circulant structure of tracking-by-detection with kernels," in ECCV, Springer, 2012.
17. Z. Kalal, J. Matas, and K. Mikolajczyk, "Pn learning: Bootstrapping binary classifiers by structural constraints," in CVPR, IEEE, 2010.
18. B. D. Lucas, T. Kanade, et al., "An iterative image registration technique with an application to stereo vision.," in IJCAI, 1981.
19. M. Ozuysal, P. Fua, and V. Lepetit, "Fast keypoint recognition in ten lines of code," in CVPR, IEEE, 2007.
20. Z. Kalal, K. Mikolajczyk, and J. Matas, "Face-tld: Tracking-learningdetection applied to faces," in ICIP, IEEE, 2010.
21. B. S. Reddy and B. N. Chatterji, "An fft-based technique for translation, rotation, and scale-invariant image registration," Image Processing, IEEE Transactions on, vol. 5, no. 8, pp. 1266-1271, 1996.