Efficient Surface Interpolation with Occlusion Detection

DOI

10.2991/jcis.2006.269How to use a DOI?

Keywords

Stereo Matching, Sparse Disparity Estimation

Abstract

In this paper we present a novel dense matching algorithm that relies on sparse stereo data in order to build a dense disparity map. The algorithm uses a recursive updating scheme to estimate the dense stereo data using various interpolation techniques. The major problem of classical template matching techniques is their reliance on a fixed template shape and poor performance around untextured regions. In this paper we attempt to alleviate the problem of template matching techniques by using an adaptive window shape and also by avoiding searching in homogenous image regions that are difficult to match by templates. The outcome is an algorithm that performs at least ten times faster than template matching, and yet it achieves higher accuracy. Moreover, our algorithm preserves depth discontinuities and assigns disparities at occluded regions.

Copyright

© 2006, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Boubakeur Boufama
AU  - Houman Rastgar
AU  - Saida Bouakaz
PY  - 2006/10
DA  - 2006/10
TI  - Efficient Surface Interpolation with Occlusion Detection
BT  - Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2006.269
DO  - 10.2991/jcis.2006.269
ID  - Boufama2006/10
ER  -