Scene Flow from Depth and Color Images

Antoine Letouzey 1 Benjamin Petit 1 Edmond Boyer 1
1 MORPHEO - Capture and Analysis of Shapes in Motion
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : In this paper we consider the problem of estimating a 3D motion field using multiple cameras. In particular, we focus on the situation where a depth camera and one or more color cameras are available, a common situation with recent composite sensors such as the Kinect. In this case, geometric information from depth maps can be combined with intensity variations in color images in order to estimate smooth and dense 3D motion fields. We propose a unified framework for this purpose, that can handle both arbitrary large motions and sub-pixel displacements. The estimation is cast as a linear optimization problem that can be solved very efficiently. The novelty with respect to existing scene flow approaches is that it takes advantage of the geometric information provided by the depth camera to define a surface domain over which photometric constraints can be consistently integrated in 3D. Experiments on real and synthetic data provide both qualitative and quantitative results that demonstrate the interest of the approach.
Type de document :
Communication dans un congrès
Jesse Hoey and Stephen McKenna and Emanuele Trucco. BMVC 2011 - British Machine Vision Conference, Aug 2011, Dundee, United Kingdom. BMVA Press, pp.46:1-11, 2011, Proceedings of the British Machine Vision Conference. 〈10.5244/C.25.46〉
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Soumis le : lundi 22 août 2011 - 12:37:42
Dernière modification le : jeudi 25 juin 2015 - 01:01:31
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Antoine Letouzey, Benjamin Petit, Edmond Boyer. Scene Flow from Depth and Color Images. Jesse Hoey and Stephen McKenna and Emanuele Trucco. BMVC 2011 - British Machine Vision Conference, Aug 2011, Dundee, United Kingdom. BMVA Press, pp.46:1-11, 2011, Proceedings of the British Machine Vision Conference. 〈10.5244/C.25.46〉. 〈inria-00616353〉

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