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2020 | OriginalPaper | Buchkapitel

Confidence Map Based 3D Cost Aggregation with Multiple Minimum Spanning Trees for Stereo Matching

verfasst von : Yuhao Xiao, Dingding Xu, Guijin Wang, Xiaowei Hu, Yongbing Zhang, Xiangyang Ji, Li Zhang

Erschienen in: Pattern Recognition

Verlag: Springer International Publishing

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Abstract

Stereo matching is a challenging problem due to the mismatches caused by difficult environment conditions. In this paper, we propose an enhanced version of our previous work, denoted as 3DMST-CM, to handle challenging cases and obtain a high-accuracy disparity map based on the ambiguity of image pixels. We develop a module of distinctiveness analysis to classify pixels into distinctive and ambiguous pixels. Then distinctive pixels are utilized as anchor pixels to help match ambiguous pixels accurately. The experimental results demonstrate the effectiveness of our method and reach state-of-the-art on the Middlebury 3.0 benchmark.

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Metadaten
Titel
Confidence Map Based 3D Cost Aggregation with Multiple Minimum Spanning Trees for Stereo Matching
verfasst von
Yuhao Xiao
Dingding Xu
Guijin Wang
Xiaowei Hu
Yongbing Zhang
Xiangyang Ji
Li Zhang
Copyright-Jahr
2020
DOI
https://doi.org/10.1007/978-3-030-41404-7_25

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