Title :
Local gradient, global matching, piecewise-smooth optical flow
Author :
Ye, Ming ; Haralick, Robert M.
Author_Institution :
Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA
Abstract :
In this paper we discuss a hybrid technique for piecewise-smooth optical flow estimation. We first pose optical flow estimation as a gradient-based local regression problem and solve it under a high-breakdown robust criterion. Then taking the output from the first step as the initial guess, we recast the problem in a robust matching-based global optimization framework. We have developed novel fast-converging deterministic algorithms for both optimization problems and incorporated a hierarchical scheme to handle large motions. This technique inherits the good subpixel accuracy from the local gradient approach and the insensitivity to local perturbation and derivative quality from the global matching approach, and it overcomes the limitations of both. Significant advantages over competing techniques are demonstrated on various standard synthetic and real image sequences.
Keywords :
computer vision; image sequences; piecewise constant techniques; computer graphics; computer vision; deterministic algorithms; global matching; image sequences; local regression; optical flow estimation; piecewise smooth; video coding; Brightness; Fluid flow measurement; Image motion analysis; Image sequences; Optical saturation; Optical sensors; Optimization methods; Pollution measurement; Robustness; Velocity measurement;
Conference_Titel :
Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on
Print_ISBN :
0-7695-1272-0
DOI :
10.1109/CVPR.2001.991034