Robust multi-view correspondence of noisy 2D points using relaxation

Dong Hoon Lee; Soon Ki Jung; Kwangyun Wohn

doi:10.1049/el:20000553

Robust multi-view correspondence of noisy 2D points using relaxation

Dong Hoon Lee, Soon Ki Jung, Kwangyun Wohn

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Abstract

An efficient ghost removal algorithm for reliably extracting correspondence information for 2D points from several views using epipolar constraints is proposed. The point matching relations are modelled using a weighted k-partite graph and a globally convergent iterative algorithm is used to extract reliable maximum cliques from the graph using probabilistic relaxation labelling. Experimental results show the effectiveness of the proposed method.

Original language	English
Pages (from-to)	719-720
Number of pages	2
Journal	Electronics Letters
Volume	36
Issue number	8
DOIs	https://doi.org/10.1049/el:20000553
State	Published - 13 Apr 2000

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abstract = "An efficient ghost removal algorithm for reliably extracting correspondence information for 2D points from several views using epipolar constraints is proposed. The point matching relations are modelled using a weighted k-partite graph and a globally convergent iterative algorithm is used to extract reliable maximum cliques from the graph using probabilistic relaxation labelling. Experimental results show the effectiveness of the proposed method.",

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AB - An efficient ghost removal algorithm for reliably extracting correspondence information for 2D points from several views using epipolar constraints is proposed. The point matching relations are modelled using a weighted k-partite graph and a globally convergent iterative algorithm is used to extract reliable maximum cliques from the graph using probabilistic relaxation labelling. Experimental results show the effectiveness of the proposed method.

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Robust multi-view correspondence of noisy 2D points using relaxation

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