Local gradient, global matching, piecewise-smooth optical flow

M. Ye, R.A. Haralick
Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001  
In this paper we discuss a hybrid technique for piecewisesmooth 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 fastconverging deterministic algorithms for both optimization problems and incorporated a hierarchical
more » ... heme 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.
doi:10.1109/cvpr.2001.991034 dblp:conf/cvpr/YeH01 fatcat:yttmbhftkrenxlylktw3pxgpzm