Joint tracking of features and edges

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Birchfield, Stanley T ^a   Pundlik, Shrinivas J ^a  

^a AMRL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; FEATURE EXTRACTION; IMAGE PROCESSING; PATTERN RECOGNITION;

IMAGE SEQUENCING; JOINT TRACKING; LUCAS-KANADE;

ESTIMATION;

EID: 51949095807     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587486     Document Type: Conference Paper

References (23)

1. S. Baker and I. Matthews. Lucas-Kanade 20 years on: A unifying framework. International Journal of Computer Vision, 56(3):221-255, 2004.
2. S. Baker, D. Scharstein, J. Lewis, S. Roth, M. J. Black, and R. Szeliski. A database and evaluation methodology for optical flow. In Proceedings of the International Conference on Computer Vision, 2007.
3. J.-Y. Bouguet. Pyramidal implementation of the Lucas Kanade feature tracker. OpenCV documentation, Intel Corporation, Microprocessor Research Labs, 1999.
4. A. Bruhn, J. Weickert, and C. Schnörr. Lucas/Kanade meets Horn/Schunck: Combining local and global optic flow methods. International Journal of Computer Vision, 61(3):211-231, 2005.
5. J. Costeira and T. Kanade. A multi-body factorization method for motion analysis. In Proceedings of the International Conference on Computer Vision, pages 1071-1076, 1995.
6. D. DeCarlo and D. Metaxas. Optical flow constraints on deformable models with applications to face tracking. International Journal of Computer Vision, 38(2):99-127, July 2000.
7. G. D. Hager and P. N. Belhumeur. Efficient region tracking with parametric models of geometry and illumination. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(10):1025-1039, Oct. 1998.
8. B. K. P. Horn and B. G. Schunck. Determining optical flow. Artificial Intelligence, 17(185):185-203, 1981.
9. H. Jin, P. Favaro, and S. Soatto. Real-time 3-D motion and structure of point features: Front-end system for vision-based control and interaction. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2000.
10. H. Jin, P. Favaro, and S. Soatto. Real-time feature tracking and outlier rejection with changes in illumination. In Proceedings of the International Conference on Computer Vision, 2001.
11. N. K. Kanhere, S. J. Pundlik, and S. T. Birchfield. Vehicle segmentation and tracking from a low-angle off-axis camera. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 1152-1157, June 2005.
12. S. J. Kim, J.-M. Frahm, and M. Pollefeys. Joint feature tracking and radiometric calibration from auto-exposure video. In Proceedings of the International Conference on Computer Vision, 2007.
13. R. Lublinerman, M. Sznaier, and O. Camps. Dynamics based robust motion segmentation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 1176-1184, 2006.
14. B. D. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. In Proceedings of the 7th International Joint Conference on Artificial Intelligence, pages 674-679, 1981.
15. I. Matthews, T. Ishikawa, and S. Baker. The template update problem. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(6):810-815, June 2004.
16. F. Rothganger, S. Lazebnik, C. Schmid, and J. Ponce. Segmenting, modeling, and matching video clips containing multiple moving objects. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 477-491, 2004.
17. J. Shi and C. Tomasi. Good features to track. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 593-600, 1994.
18. J. Sivic, F. Schaffalitzky, and A. Zisserman. Object level grouping for video shots. In Proceedings of the European Conference on Computer Vision, volume 2, pages 85-98, 2004.
19. C. Tomasi and T. Kanade. Shape and motion from image streams under orthography: A factorization method. International Journal of Computer Vision, 9(2):137-154, 1992.
20. T. Tommasini, A. Fusiello, E. Trucco, and V. Roberto. Making good features track better. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1998.
21. L. Torresani, D. Yang, G. Alexander, and C. Bregler. Tracking and modelling non-rigid objects with rank constraints. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2001.
22. S. Šegvić, A. Remazeilles, and F. Chaumette. Enhancing the point feature tracker by adaptive modelling of the feature support. In Proceedings of the European Conference on Computer Vision, pages 112-124, 2006.
23. S. Zhilong and R. Qiuqi. Image registration based on KLT feature tracker in image mosaicing application. In Proceedings of the 5th International Conference on Signal Processing (ICSP), volume 2, pages 1143-1146, 2000.