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http://dx.doi.org/10.5909/JBE.2008.13.5.685

Joint Segmentation of Multi-View Images by Region Correspondence  

Lee, Soo-Chahn (School of Electrical Engineering and Computer Science, Seoul National Univ.)
Kwon, Dong-Jin (School of Electrical Engineering and Computer Science, Seoul National Univ.)
Yun, Il-Dong (School of Digital Information Engineering, Hankuk University of Foreign Studies)
Lee, Sang-Uk (School of Electrical Engineering and Computer Science, Seoul National Univ.)
Publication Information
Journal of Broadcast Engineering / v.13, no.5, 2008 , pp. 685-695 More about this Journal
Abstract
This paper presents a method to segment the object of interest from a set of multi-view images with minimal user interaction. Specifically, after the user segments an initial image, we first estimate the transformations between foreground and background of the segmented image and the neighboring image, respectively. From these transformations, we obtain regions in the neighboring image that respectively correspond to the foreground and the background of the segmented image. We are then able to segment the neighboring image based on these regions, and iterate this process to segment the whole image set. Transformation of foregrounds are estimated by feature-based registration with free-form deformation, while transformation of backgrounds are estimated by homography constrained to affine transformation. Here, both are based on correspondence point pairs. Segmentation is done by estimating pixel color distributions and defining a shape prior based on the obtained foreground and background regions and applying them to a Markov random field (MRF) energy minimization framework for image segmentation. Experimental results demonstrate the effectiveness of the proposed method.
Keywords
Multi-view images; Image Segmentation; Region Correspondence; MRF Energy minimization; Shape prior;
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