Tree structural watershed for stereo matchingShow others and affiliations
2012 (English)In: IVCNZ '12, Proceedings of the 27th Conference on Image and Vision Computing New Zealand, ACM Digital Library, 2012, p. 340-345Conference paper, Published paper (Other academic)
Resource type
Text
Abstract [en]
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.
Place, publisher, year, edition, pages
ACM Digital Library, 2012. p. 340-345
Keywords [en]
Watershed optimization, Region combination, Stereo, Disparity calculation
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-125062DOI: 10.1145/2425836.2425903ISBN: 9781450314732 (print)OAI: oai:DiVA.org:liu-125062DiVA, id: diva2:902693
Conference
27th Image and Vision Computing New Zealand, IVCNZ'12, Dunedin, New Zealand, November 26-28th 2012
2016-02-122016-02-122016-02-22Bibliographically approved