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Authors: Junlei Ma ; Dianle Zhou ; Chen Chen and Wei Wang

Affiliation: National University of Defense Technology, China

Keyword(s): Stereo matching, Automatic matting, Iterative optimization.

Related Ontology Subjects/Areas/Topics: Applications ; Computer Vision, Visualization and Computer Graphics ; Geometry and Modeling ; Image Understanding ; Image-Based Modeling ; Object Recognition ; Pattern Recognition ; Software Engineering

Abstract: This study presents a novel iterative algorithm of joint depth and alpha matte optimization via stereo (JDMOS). This algorithm realizes simultaneous estimation of depth map and matting image to obtain final convergence. The depth map provides depth information to realize automatic image matting, whereas the border details generated from the image matting can refine the depth map in boundary areas. Compared with monocular matting methods, another advantage offered by JDMOS is that the image matting process is completely automatic, and the result is significantly more robust when depth information is introduced. The major contribution of JDMOS is adding image matting information to the cost function, thereby refining the depth map, especially in the scene boundary. Similarly, optimized disparity information is stitched into the matting algorithm as prior knowledge to make the foreground–background segmentation more accurate. Experimental results on Middlebury datasets demonstr ate the effectiveness of JDMOS. (More)

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Paper citation in several formats:
Ma, J.; Zhou, D.; Chen, C. and Wang, W. (2017). Joint Depth and Alpha Matte Optimization via Stereo. In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-222-6; ISSN 2184-4313, SciTePress, pages 426-433. DOI: 10.5220/0006191304260433

@conference{icpram17,
author={Junlei Ma. and Dianle Zhou. and Chen Chen. and Wei Wang.},
title={Joint Depth and Alpha Matte Optimization via Stereo},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2017},
pages={426-433},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006191304260433},
isbn={978-989-758-222-6},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Joint Depth and Alpha Matte Optimization via Stereo
SN - 978-989-758-222-6
IS - 2184-4313
AU - Ma, J.
AU - Zhou, D.
AU - Chen, C.
AU - Wang, W.
PY - 2017
SP - 426
EP - 433
DO - 10.5220/0006191304260433
PB - SciTePress