Consensus-based matching and tracking of keypoints for object tracking

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

Volumn , Issue , 2014, Pages 862-869

  Nebehay, Georg ^a   Pflugfelder, Roman ^a  

^a AIT AUSTRIAN INSTITUTE OF TECHNOLOGY   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

TRACKING (POSITION);

DESCRIPTORS; IMAGE SPACE; KEY-POINT DETECTORS; KEYPOINTS; MODEL FREE; OBJECT TRACKING; OUTLIER DETECTION; SCALE AND ROTATION;

IMAGE PROCESSING;

EID: 84904695947     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WACV.2014.6836013     Document Type: Conference Paper

References (30)

1. A. Adam, E. Rivlin, and I. Shimshoni. Robust fragmentsbased tracking using the integral histogram. In CVPR, 2006
2. B. Babenko, M.-H. Yang, and S. Belongie. Robust object tracking with online multiple instance learning. TPAMI, 33(8), 2011
3. D. H. Ballard. Generalizing the hough transform to detect arbitrary shapes. IJPRAI, 13(2), 1981
4. S. Duffner and C. Garcia. PixelTrack: A fast adaptive algorithm for tracking non-rigid objects . In ICCV, 2013
5. J. Gall, A. Yao, N. Razavi, L. Van Gool, and V. Lempitsky. Hough forests for object detection, tracking, and action recognition. TPAMI, 33(11), 2011
6. M. Godec, P. M. Roth, and H. Bischof. Hough-based tracking of non-rigid objects. In ICCV, 2011
7. H. Grabner and H. Bischof. On-line boosting and vision. In CVPR, 2006
8. H. Grabner, C. Leistner, and H. Bischof. Semi-supervised On-Line boosting for robust tracking. In ECCV, 2008
9. M. Grabner, H. Grabner, and H. Bischof. Learning features for tracking. In CVPR, 2007
10. S. Hare, A. Saffari, and P. H. S. Torr. Struck: Structured output tracking with kernels. In ICCV, 2011
11. S. Hare, A. Saffari, and P. H. S. Torr. Efficient online structured output learning for keypoint-based object tracking. In CVPR, 2012
12. B. Hemery, H. Laurent, and C. Rosenberger. Comparative study of metrics for evaluation of object localisation by bounding boxes. In ICIG, 2007
13. G. Hua and Y.Wu. Measurement integration under inconsistency for robust tracking. In CVPR, 2006
14. Z. Kalal, K. Mikolajczyk, and J. Matas. Tracking-Learningdetection. TPAMI, 34(7), 2012
15. B. Leibe, A. Leonardis, and B. Schiele. Robust object detection with interleaved categorization and segmentation. IJCV, 77(1-3), 2008
16. S. Leutenegger, M. Chli, and R. Y. Siegwart. BRISK: Binary robust invariant scalable keypoints. In ICCV, 2011
17. T. List, J. Bins, J. Vazquez, and R. B. Fisher. Performance evaluating the evaluator. In PETS, 2005
18. D. G. Lowe. Distinctive image features from Scale-Invariant keypoints. IJCV, 60(2), 2004
19. B. D. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. In IJCAI, 1981
20. E. Maggio and A. Cavallaro. Video Tracking: Theory and Practice. 2011
21. M. E. Maresca and A. Petrosino. MATRIOSKA: A multilevel approach to fast tracking by learning. In ICIAP, 2013
22. M. Özuysal, M. Calonder, V. Lepetit, and P. Fua. Fast keypoint recognition using random ferns. TPAMI, 32(3), 2010
23. M. Özuysal, V. Lepetit, F. Fleuret, and P. Fua. Feature harvesting for Tracking-by-Detection. In ECCV. 2006
24. E. Rosten, R. Porter, and T. Drummond. Faster and better: A machine learning approach to corner detection. TPAMI, 32(1), 2010
25. A. Saffari, C. Leistner, J. Santner, M. Godec, and H. Bischof. On-line random forests. In ICCV Workshops, 2009
26. J. Santner, C. Leistner, A. Saffari, T. Pock, and H. Bischof. PROST: Parallel robust online simple tracking. In CVPR, 2010
27. S. M. Shahed Nejhum, J. Ho, and M.-H. Yang. Visual tracking with histograms and articulating blocks. In CVPR, 2008
28. Y. Wu, J. Lim, and M.-H. Yang. Online object tracking: A benchmark. In CVPR, 2013
29. R. Xu and D.Wunsch. Survey of clustering algorithms. TNN, 16(3), 2005
30. L. Zhang and L. Van Der Maaten. Structure preserving object tracking. In CVPR, 2013.