Multispectral constraints for optical flow computation

Multispectral constraints are exploited for optical flow computation. The theoretical basis and conditions for using multispectral images are described. An optical flow algorithm using multispectral constraints is outlined. Tests of the algorithm on real image sequences show that various multispectral constraints from the visible and infrared spectrum can be used to compute optical flow fields in the presence of noise.<<ETX>>

[1]  Hsien-Che Lee,et al.  Modeling Light Reflection for Computer Color Vision , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Brian G. Schunck,et al.  Image Flow: Fundamentals and Algorithms , 1988 .

[3]  Larry S. Davis,et al.  Motion estimation based on multiple local constraints and nonlinear smoothing , 1983, Pattern Recognit..

[4]  Yuan-Fang Wang,et al.  Experiments in computing optical flow with the gradient-based, multiconstraint method , 1987, Pattern Recognit..

[5]  S. Negahdaripour,et al.  Relaxing the Brightness Constancy Assumption in Computing Optical Flow , 1987 .

[6]  Berthold K. P. Horn.  Robot vision , 1986, MIT electrical engineering and computer science series.

[7]  Tomaso A. Poggio,et al.  On Edge Detection , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  A. Verri,et al.  Constraints for the computation of optical flow , 1989, [1989] Proceedings. Workshop on Visual Motion.

[9]  A. Verri,et al.  Analysis of differential and matching methods for optical flow , 1989, [1989] Proceedings. Workshop on Visual Motion.