Modified Region Growing for Stereo of Slant and Textureless Surfaces

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.

• Type: Conference
• Year: 2010
• Where: ISVC
• Authors: Rohith MV, Gowri Somanath, Chandra Kambhamettu, Cathleen Geiger, and David Finnegan
• Keywords: ISVC 2010, Large Scale Reconstruction, Large Scale Stereo, Region Growing, Sea Ice 3d Reconstruction, Stereo