Robust computation of optical flow under non-uniform illumination variations

Proceedings - International Conference on Pattern Recognition

Volumn 16, Issue 1, 2002, Pages 327-330

  Teng, Chin Hung ^a   Lai, Shang Hong ^a   Chen, Yung Sheng ^b   Hsu, Wen Hsing ^a,c  

^a NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^b YUAN ZE UNIVERSITY   (Taiwan)

^c INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; LIGHTING; LINEAR EQUATIONS; OPTICAL FLOWS; PARAMETER ESTIMATION; ROBUSTNESS (CONTROL SYSTEMS); ALGORITHMS; COMPUTER VISION; INERTIAL CONFINEMENT FUSION; LINEAR SYSTEMS; PIXELS;

ENERGY MINIMIZATION METHOD; NON-UNIFORM ILLUMINATION; PIXEL-TO-PIXEL VARIATION; WEIGHTING SCHEME;

COMPUTATION THEORY; PATTERN RECOGNITION;

ENERGY MINIMIZATION METHODS; ILLUMINATION FIELDS; ILLUMINATION VARIATION; NON-UNIFORM ILLUMINATION; PRECONDITIONED CONJUGATE GRADIENT ALGORITHMS; REAL IMAGE SEQUENCES; SMOOTHNESS CONSTRAINTS; STATISTICAL PROPERTIES;

EID: 33751572609     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (12)

1. A. Verri, and T. Poggio, "Motion Field and Optical Flow: Qualitative Properties". IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 11, no. 5, 1989, pp. 490-498.
2. A. Nomura, H. Miike, and K. Koga, "Determining Motion Fields under Non-uniform Illumination", Pattern Recognition Letter, vol. 16, 1995, pp. 285-296.
3. S. Negahdaripour, "Revised Definition of Optical Flow: Integration of Radiometric and Geometric Cues for Dynamic Scene Analysis. IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 9, 1998, pp. 961-979.
4. H. W. Haussecker, and D. J. Fleet, "Computing Optical Flow with Physical Models of Brightness Variation", IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, no. 6, 2001, pp. 661-673.
5. F. J. Hampson, and J.-C. Resquet, "Motion Estimation in the Presence of Illumination Variations". Signal Processing: Image Communication, vol. 16, 2000, pp. 373-
6. 381 Nomura, "Spatio-Temproal Optimization Method for Determining Motion Vector Fields under Non-stationary Il-lumination", Image and Vision Computing, vol. 18, 2000, pp. 939-950.
7. L. Zhang, T. Sakurai, and H. Miike, "Detection of Motion Fields under Spatio-Temproal Non-uniform Illumination", Image and Vision Computing, vol. 17, 1999, pp. 309-320.
8. S.-H. Lai, and B. C. Vermin, "Reliable and Efficient Computation of Optical Flow", International Journal of Computer Vision, vol. 29, no. 2, 1998, pp. 87-105.
9. G. H. Golub and C. F. Van Loan, Matrix Computations. 2nd edition, The Johns Hopkins University Press, 1989.
10. S.-H. Lai, "Robust Image Matching under Partial Occlusion and Spatially Varying Illumination Change", Computer Vision and Image Understanding, vol. 78, 2000, pp.84-98.
11. G. Li, Robust regression, in Exploring Data Tables, Trends, and Shapes (D. C.Hoaglin, F.Mosteller and J. W. Tukey, Eds.), pp. 281-343, VViely, New York, 1985.
12. J. L. Barron, D. J. Fleet, S. S. Beauchemin, "Performance of Optical Flow Techniques", International Journal of Computer Vision, vol. 12, no. 1, 1994, pp. 43-77.