Resolving motion correspondence for densely moving points

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 23, Issue 1, 2001, Pages 54-72

  Veenman, Cor J ^a,b   Reinders, Marcel J T ^a,b   Backer, Eric ^a,b  

^a IEEE   (Netherlands)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

FEATURE POINT TRACKING; MOTION CORRESPONDENCE; QUALITATIVE MODELING; TARGET TRACKING;

ARTIFICIAL INTELLIGENCE; COMPUTER VISION; CONSTRAINT THEORY; ERROR DETECTION; FEATURE EXTRACTION; GENETIC ALGORITHMS; MATHEMATICAL MODELS; OPTIMIZATION; PATTERN RECOGNITION; PROBABILITY DENSITY FUNCTION; STATISTICAL METHODS; VECTORS;

IMAGE UNDERSTANDING;

EID: 0035116552     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/34.899946     Document Type: Article

References (27)

1. D. Chetverikov and J. Verestoy, Feature Point Tracking for Incomplete Trajectories, Computing, vol. 62, pp. 321-338, 1999.
2. I.J. Cox, A Review of Statistical Data Association Techniques for Motion Correspondence, Int'l J. Computer Vision, vol. 10, no. 1, pp. 53-66, 1993.
3. I.J. Cox and S.L. Hingorani, An Efficient Implementation of Reid's Multiple Hypothesis Tracking Algorithm and Its Evaluation for the Purpose of Visual Tracking, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 18, no. 2, pp. 138-150, Feb. 1996.
4. I.J. Cox and M.L. Miller, On Finding Ranked Assignments with Applications to Multitarget Tracking and Motion Correspondence, IEEE Trans. Aerospace and Electronic Systems, vol. 32, no. 1, pp. 486-489, Jan. 1995.
5. I.J. Cox, M.L. Miller, R. Danchick, and G.E. Newnam, A Comparison of Two Algorithms for Determining Ranked Assignments with Application to Multitarget Tracking and Motion Correspondence, IEEE Trans. Aerospace and Electronic Systems, vol. 33, no. 1, pp. 295-300, Jan. 1997.
6. R. Danchick and G.E. Newnam, A Fast Method for Finding the Exact n-Best Hypotheses for Multitarget Tracking, IEEE Trans. Aerospace and Electronic Systems, vol. 29, no. 2, pp. 555-560, Apr. 1993.
7. S. Deb, K.R. Pattipati, and Y. Bar-Shalom, A New Algorithm for the Generalized Multidimensional Assignment Problem, Proc. IEEE Int'l Conf. Systems, Man and Cybernetics; Emergent Innovations in Information Transfer Processing and Decision Making, pp. 249-254, 1992.
8. S. Deb, M. Yeddanapudi, K. Pattipati, and Y. Bar-Shalom, A Generalized S-D Assignment agorithm for Multisensor-Multitarget State Estimation, IEEE Trans. Aerospace and Electronic Systems, vol. 33, no. 2, pp. 523-538, 1997.
9. T.E. Fortmann, Y. Bar-Shalom, and M. Sheffe, Sonar Tracking of Multiple Targets Using Joint Probabilistic Data Association, IEEE J. Oceanic Eng., vol. 8, no. 3, pp. 173-184, July 1983.
10. K.I. Hodges, Adaptive Constraints for Feature Tracking, Monthly Weather Rev., vol. 127, pp. 1362-1373, 1998.
11. B.K.P. Horn and B.G. Schunck, Determining Optical Flow, Artificial Intelligence, vol. 17, pp. 185-203, 1981.
12. V.S.S. Hwang, Tracking Feature Points in Time-Varying Images Using an Opportunistic Selection Approach, Pattern Recognition, vol. 22, no. 3, pp. 247-256, 1989.
13. H.W. Kuhn, The Hungarian Method for Solving the Assignment Problem, Naval Research Logistics Quarterly, vol. 2, pp. 83-97, 1955.
14. R. Mehrotra, Establishing Motion-Based Feature Point Correspondence, Pattern Recognition, vol. 31, no. 2, pp. 23-30, 1998.
15. M.L. Miller, H.S. Stone, and I.J. Cox, Optimizing Murty's Ranked Assignment Method, IEEE Trans. Aerospace and Electronic Systems, vol. 33, no. 3, pp. 851-861, 1997.
16. V. Nagarajan, M.R. Chidambara, and R.N. Sharma, Combinatorial Problems in Multitarget Tracking - A Comprehensive Solution, IEE Proc., vol. 134, no. 1, pp. 113-118, Feb. 1987.
17. A. B. Poore, Multidimensional Assignments and Multitarget Tracking, Proc. Partitioning Data Sets, DIMACS Workshop, pp. 169-196, 1995.
18. A.B. Poore and X. Yan, Data Association in Multiframe Processing, Proc. Second Int'l Conf. Information Fusion, vol. II, pp. 1037-1044, 1999.
19. K. Rangarajan and M. Sha, Establishing Motion Correspondence, CVGIP: Image Understanding, vol. 24, no. 6, pp. 56-73, July 1991.
20. D.B. Reid, An Algorithm for Tracking Multiple Targets, IEEE Trans. Automatic Control, vol. 24, no. 6, pp. 843-854, Dec. 1979.
21. V. Salari and I.K. Sethi, Feature Point Correspondence in the Presence of Occlusion, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 1, pp. 97-91, Jan. 1990.
22. I.K. Sethi and R. Jain, Finding Trajectories of Feature Points in a Monocular Image Sequence, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 9, no. 1, pp. 56-73, Jan. 1987.
23. P.J. Shea and A.B. Poore, Computational Experiences with Hot Starts for a Moving Window Implementation of Track Maintanance, Proc. SPIE: Int'l Soc. Optical Eng., vol. 3373, pp. 428-439, 1998.
24. R.Y. Tsai and T.S. Huang, Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surface, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 6, no. 1, pp. 13-26, Jan. 1984.
25. S. Ullman, The Interpretation of Visual Motion. Cambridge, Mass.: MIT Press, 1979.
26. J. Verestoy and D. Chetverikov, Experimental Comparative Evaluation of Feature Point Tracking Algorithms, Proc. Workshop Evaluation and Validation of Computer Vision Algorithms, pp. 183-194, 2000.
27. C.J. Veenman, E.H. Hendriks, and M.J.T. Reinders, A Fast and Robust Point Tracking Algorithm, Proc. IEEE Int'l Conf. on Image Processing, vol. 3, pp. 653-657, Oct. 1998.