This chapter provides a tutorial introduction to gradient-based optical flow estimation. We discuss least-squares and robust estimators, iterative coarse-to-fine refinement, different forms of parametric motion models, different conservation assumptions, probabilistic formulations, and robust mixture models. © 2006 Springer Science+Business Media, Inc.
CITATION STYLE
Fleet, D., & Weiss, Y. (2006). Optical flow estimation. In Handbook of Mathematical Models in Computer Vision (pp. 237–257). Springer US. https://doi.org/10.1007/0-387-28831-7_15
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