DocumentCode :
3284710
Title :
Local/global scene flow estimation
Author :
Quiroga, Julian ; Devernay, Frederic ; Crowley, J.
Author_Institution :
PRIMA team, INRIA Grenoble Rhone-Alpes, Grenoble, France
fYear :
2013
fDate :
15-18 Sept. 2013
Firstpage :
3850
Lastpage :
3854
Abstract :
The scene flow describes the 3D motion of every point in a scene between two time steps. We present a novel method to estimate a dense scene flow using intensity and depth data. It is well known that local methods are more robust under noise while global techniques yield dense motion estimation. We combine local and global constraints to solve for the scene flow in a variational framework. An adaptive TV (Total Variation) regularization is used to preserve motion discontinuities. Besides, we constrain the motion using a set of 3D correspondences to deal with large displacements. In the experimentation our approach outperforms previous scene flow from intensity and depth methods in terms of accuracy.
Keywords :
computer vision; motion estimation; variational techniques; 3D correspondence; 3D motion; adaptive TV regularization; adaptive total variation regularization; dense motion estimation; dense scene flow; depth data; global constraint; global scene flow estimation; intensity data; local constraint; local scene flow estimation; variational framework; 3D motion; Scene flow; depth data; variational;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
Type :
conf
DOI :
10.1109/ICIP.2013.6738793
Filename :
6738793
Link To Document :
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