9th Joint International Conference on Information Sciences (JCIS-06)

Efficient Surface Interpolation with Occlusion Detection

Authors
Boubakeur Boufama 0, Houman Rastgar, Saida Bouakaz
Corresponding Author
Boubakeur Boufama
0University of Windsor
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DOI
https://doi.org/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.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Publication Date
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ISBN
978-90-78677-01-7
DOI
https://doi.org/10.2991/jcis.2006.269How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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