Cited By
View all- Tan XSun CSirault XFurbank RPham T(2014)Stereo matching using cost volume watershed and region mergingImage Communication10.1016/j.image.2014.06.00229:10(1232-1244)Online publication date: 1-Nov-2014
Tree structural watershed for stereo matching
Pages 340 - 345
Abstract
We present a new method for dense stereo matching based on a tree structural cost volume watershed (TSCVW) and a region combination (RC) process. Given a cost volume as the data cost and an initial segmentation result, the proposed TSCVW method reliably estimates the disparities in a segment by using energy optimization to control plane segmentation and plane fitting. Then the disparities in the incorrectly fitted and occluded regions are refined using our RC process. Experimental results show that our method is very robust to different initial segmentation results and the shape of a segment. The comparison between our algorithm and the current state-of-the-art algorithms on the Middlebury website shows that our algorithm is very competitive.
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Published: 26 November 2012
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View all- Tan XSun CSirault XFurbank RPham T(2014)Stereo matching using cost volume watershed and region mergingImage Communication10.1016/j.image.2014.06.00229:10(1232-1244)Online publication date: 1-Nov-2014
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