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Graph Cut Based Multiple View Segmentation for 3D Reconstruction

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3 Author(s)
Mario Sormann ; VRVis Research Center, Austria ; Christopher Zach ; Konrad Karner

In this paper we propose a novel framework for efficiently extracting foreground objects in so called short-baseline image sequences. We apply the obtained segmentation to improve subsequent 3D reconstruction results. Essentially, our framework combines a graph cut based optimization algorithm with an intuitive user interface. At first a meanshift segmentation algorithm partitions each image of the sequence into a certain number of regions. Additionally we provide an intelligent graphical user interface for easy specification of foreground as well as background regions across all images of the sequence. Within the graph cut optimization algorithm we define new energy terms to increase the robustness and to keep the segmentation of the foreground object coherent across all images of the sequence. Finally, a refined graph cut segmentation and several adjustment operations allow an accurate and effective foreground extraction. The obtained results are demonstrated on several real world data sets.

Published in:

3D Data Processing, Visualization, and Transmission, Third International Symposium on

Date of Conference:

14-16 June 2006