Modified region growing for stereo of slant and textureless surfaces

Authors:
M. V. Rohith;Gowri Somanath;Chandra Kambhamettu;Cathleen Geiger;David Finnegan
Affiliations:
Video, Image Modeling and Synthesis Lab., Department of Computer and Information Sciences, University of Delaware, Newark, DE;Video, Image Modeling and Synthesis Lab., Department of Computer and Information Sciences, University of Delaware, Newark, DE;Video, Image Modeling and Synthesis Lab., Department of Computer and Information Sciences, University of Delaware, Newark, DE;Department of Geography, University of Delaware, Newark, DE;U.S. Army Corps of Engineers, Cold Regions Research and Engineering Laboratory, Hanover, NH
Venue:
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Year:
2010

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Abstract

In this paper, we present an algorithm for estimating disparity for images containing large textureless regions. We propose a fast and efficient region growing algorithm for estimating the stereo disparity. Though we present results on ice images, the algorithm can be easily used for other applications. We modify the first-best region growing algorithm using relaxed uniqueness constraints and matching for sub-pixel values and slant surfaces. We provide an efficient method for matching multiple windows using a linear transform. We estimate the parameters required by the algorithm automatically based on initial correspondences. Our method was tested on synthetic, benchmark and real outdoor data. We quantitatively demonstrated that our method performs well in all three cases.