Dense optical flow estimation from the monogenic curvature tensor

Authors:
Di Zang;Lennart Wietzke;Christian Schmaltz;Gerald Sommer
Affiliations:
Department of Computer Science, Christian-Albrechts-University of Kiel, Germany;Department of Computer Science, Christian-Albrechts-University of Kiel, Germany;Faculty of Mathematics and Computer Science, Saarland University, Germany;Department of Computer Science, Christian-Albrechts-University of Kiel, Germany
Venue:
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Year:
2007

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Abstract

In this paper, we address the topic of estimating two-frame dense optical flow from the monogenic curvature tensor. The monogenic curvature tensor is a novel image model, from which local phases of image structures can be obtained in a multi-scale way. We adapt the combined local and global (CLG) optical flow estimation approach to our framework. In this way, the intensity constraint equation is replaced by the local phase vector information. Optical flow estimation under the illumination change is investigated in detail. Experimental results demonstrate that our approach gives accurate estimation and is robust against noise contamination. Compared with the intensity based approach, the proposed method shows much better performance in estimating flow fields under brightness variations.