Towards multiple-orientation based tensor invariants for object tracking

European Signal Processing Conference

Volumn , Issue , 2006, Pages

  Stache, Nicolaj C ^a   Stehle, Thomas H ^a   Mühlich, Matthias ^a   Aach, Til ^a  

^a RWTH AACHEN UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EIGEN-VALUE; EIGENVALUES; LEAST SQUARE; LOCAL REGION; NEIGHBOURHOOD; OBJECT TRACKING; OPTICAL FLOW ESTIMATION; ORIENTATION STRUCTURE; ROTATION INVARIANT; SCALE-INVARIANT; SPATIAL IMAGES; STRUCTURE TENSORS; TENSOR INVARIANTS; X-JUNCTION;

EIGENVALUES AND EIGENFUNCTIONS; ESTIMATION; OPTICAL FLOWS; SIGNAL PROCESSING;

TENSORS;

EID: 78651112584     PISSN: 22195491     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. T. Aach, I. Stuke, C. Mota, and E. Barth. Estimation of multiple local orientations in image signals. Proc. IEEE ICASSP-2004:III 553-556,Montreal,May 17-21 2004.
2. J. Bigün and G. H. Granlund. Optimal orientation detection of linear symmetry. In Proceedings IEEE First International Conference on Computer Vision, pages 433-438, London, June 1987.
3. S. Di Zenzo. A note on the gradient of a multiimage. Computer Vision, Graphics, and Image Processing, 33:116-125, 1986.
4. M. Elad, P. Teo, and Y. Hel-Or. On the design of optimal filters for gradient-based motion. International Journal of Computer Vision, page submitted, 2002.
5. D. A. Forsyth and J. Ponce. Computer Vision. A Modern Approach. Prentice-Hall, Upper Saddle River, 2003.
6. B. K. P. Horn and B. G. Schunck. Determining optical flow. Artificial Intelligence, 17:185-203, 1981.
7. M. Kass and A. Witkin. Analyzing oriented patterns. Computer Vision, Graphics, and Image Processing, 37:362-385, 1987.
8. B. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. In 7th International Joint Conference on Artificial Intelligence, pages 674-679, Vancouver, 1981.
9. C. Mota, T. Aach, I. Stuke, and E. Barth. Estimation of multiple orientations in multi-dimensional signals. In IEEE International Conference on Image Processing (ICIP), pages 2665-2668, and on CD-ROM: ISBN 0-7803-8555-1, Singapore, Oct. 24-27 2004. IEEE.
10. C. Mota, I. Stuke, T. Aach, and E. Barth. Estimation of multiple orientations at corners and junctions. In DAGM04: 26th Pattern Recognition Symposium, pages 163-170, Tuebingen, Aug. 30 - Sept. 1 2004. German Association for Pattern Recognition, Springer Verlag: LNCS 3175.
11. H. Scharr and B. Jähne. Optimization of spatiotemporal filter families for fast and accurate motion estimation. In Image Sequence Analysis to Investigate Dynamic Processes, Lecture Notes in Computer Science. Springer, 2003.
12. M. Shizawa and T. Iso. Direct representation and detection of multi-scale, multi-orientation fields using local differentiation filters. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'93), pages 508-514, Piscataway, June 1993. IEEE.
13. I. Stuke, T. Aach, E. Barth, and C. Mota. Analysing superimposed oriented patterns. In 6th IEEE Southwest Symposium on Image Analysis and Interpretation, pages 133-137, Lake Tahoe, NV, March 28-30 2004. IEEE Computer Society.
14. E. Trucco and A. Verri. Introductory Techniques for 3D Computer Vision. Prentice-Hall, Upper Saddle River, 1998.
15. D. G. Lowe. Object Recognition from Local Scale-Invariant Features. In International Conference on Computer Vision, pages 1150-1157, Corfu, 1999. IEEE.