Two-stage cross-based stereo disparity refinement

Zonglin Xu; Sei Ichiro Kamata; Qieshi Zhang

doi:10.23919/MVA.2017.7986890

Two-stage cross-based stereo disparity refinement

Zonglin Xu, Sei Ichiro Kamata, Qieshi Zhang

大学院情報生産システム研究科

研究成果: Conference contribution

抄録

This paper proposed a disparity refinement method based on two-stage cross. First stage is anti-texture cross-based support region construction to build proper support regions for error pixels without being influenced by texture. Based on the support regions, second stage of the method is proposed, which is called weighted cross-based updating method. The experiments show that the proposed method could build the support region accurately and improve the accuracy of the disparity map in final results with fast speed, compared to other tree-based algorithms. It also outperforms the existing disparity refinement methods in preserving the boundaries of objects in the final disparity map.

本文言語	English
ホスト出版物のタイトル	Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
出版社	Institute of Electrical and Electronics Engineers Inc.
ページ	420-423
ページ数	4
ISBN（電子版）	9784901122160
DOI	https://doi.org/10.23919/MVA.2017.7986890
出版ステータス	Published - 2017 7 19
イベント	15th IAPR International Conference on Machine Vision Applications, MVA 2017 - Nagoya, Japan 継続期間: 2017 5 8 → 2017 5 12

出版物シリーズ

名前	Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017

Other

Other	15th IAPR International Conference on Machine Vision Applications, MVA 2017
国/地域	Japan
City	Nagoya
Period	17/5/8 → 17/5/12

ASJC Scopus subject areas

コンピュータサイエンスの応用
コンピュータビジョンおよびパターン認識

文献へのアクセス

10.23919/MVA.2017.7986890

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引用スタイル

Xu, Z., Kamata, S. I., & Zhang, Q. (2017). Two-stage cross-based stereo disparity refinement. In Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017 (pp. 420-423). [7986890] (Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/MVA.2017.7986890

Two-stage cross-based stereo disparity refinement. / Xu, Zonglin; Kamata, Sei Ichiro; Zhang, Qieshi.

Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 420-423 7986890 (Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017).

研究成果: Conference contribution

Xu, Z, Kamata, SI & Zhang, Q 2017, Two-stage cross-based stereo disparity refinement. in Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017., 7986890, Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017, Institute of Electrical and Electronics Engineers Inc., pp. 420-423, 15th IAPR International Conference on Machine Vision Applications, MVA 2017, Nagoya, Japan, 17/5/8. https://doi.org/10.23919/MVA.2017.7986890

Xu Z, Kamata SI, Zhang Q. Two-stage cross-based stereo disparity refinement. In Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 420-423. 7986890. (Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017). https://doi.org/10.23919/MVA.2017.7986890

Xu, Zonglin ; Kamata, Sei Ichiro ; Zhang, Qieshi. / Two-stage cross-based stereo disparity refinement. Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 420-423 (Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017).

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abstract = "This paper proposed a disparity refinement method based on two-stage cross. First stage is anti-texture cross-based support region construction to build proper support regions for error pixels without being influenced by texture. Based on the support regions, second stage of the method is proposed, which is called weighted cross-based updating method. The experiments show that the proposed method could build the support region accurately and improve the accuracy of the disparity map in final results with fast speed, compared to other tree-based algorithms. It also outperforms the existing disparity refinement methods in preserving the boundaries of objects in the final disparity map.",

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Two-stage cross-based stereo disparity refinement

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