Abstract
In this paper, we present a segment-based stereo matching algorithm using adaptive variable windows and dynamic programming with a robust disparity. We solve the problem of window shape and size using adaptive line masks and adaptive rectangular windows which are constrained by segments and visibility that reduces ambiguity produced by the occlusion in the computation window. In dynamic programming, we also propose the method that selects an efficient occlusion penalty.
This work was partially supported by the Brain Korea 21 Project and KIPA-Information Technology Research Center.
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© 2005 Springer-Verlag Berlin Heidelberg
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Dong, WP., Lee, YS., Jeong, CS. (2005). A Stereo Matching Using Variable Windows and Dynamic Programming. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_186
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DOI: https://doi.org/10.1007/11589990_186
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30462-3
Online ISBN: 978-3-540-31652-7
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