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

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings of the 15th IAPR International Conference on Machine Vision Applications, MVA 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	420-423
Number of pages	4
ISBN (Electronic)	9784901122160
DOIs	https://doi.org/10.23919/MVA.2017.7986890
Publication status	Published - 2017 Jul 19
Event	15th IAPR International Conference on Machine Vision Applications, MVA 2017 - Nagoya, Japan Duration: 2017 May 8 → 2017 May 12

Publication series

Name	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
Country/Territory	Japan
City	Nagoya
Period	17/5/8 → 17/5/12

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition

Access to Document

10.23919/MVA.2017.7986890

Cite this

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). Article 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).

Research output: Chapter in Book/Report/Conference proceeding › 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). doi: 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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AB - 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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