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Self-Similarity Based Corresponding-Point Extraction from Weakly Textured Stereo Pairs
Joint Authors
Ding, Yongsheng
Hao, Kuangrong
Mao, Min
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-09-03
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
For the areas of low textured in image pairs, there is nearly no point that can be detected by traditional methods.
The information in these areas will not be extracted by classical interest-point detectors.
In this paper, a novel weakly textured point detection method is presented.
The points with weakly textured characteristic are detected by the symmetry concept.
The proposed approach considers the gray variability of the weakly textured local regions.
The detection mechanism can be separated into three steps: region-similarity computation, candidate point searching, and refinement of weakly textured point set.
The mechanism of radius scale selection and texture strength conception are used in the second step and the third step, respectively.
The matching algorithm based on sparse representation (SRM) is used for matching the detected points in different images.
The results obtained on image sets with different objects show high robustness of the method to background and intraclass variations as well as to different photometric and geometric transformations; the points detected by this method are also the complement of points detected by classical detectors from the literature.
And we also verify the efficacy of SRM by comparing with classical algorithms under the occlusion and corruption situations for matching the weakly textured points.
Experiments demonstrate the effectiveness of the proposed weakly textured point detection algorithm.
American Psychological Association (APA)
Mao, Min& Hao, Kuangrong& Ding, Yongsheng. 2014. Self-Similarity Based Corresponding-Point Extraction from Weakly Textured Stereo Pairs. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-20.
https://search.emarefa.net/detail/BIM-1044374
Modern Language Association (MLA)
Mao, Min…[et al.]. Self-Similarity Based Corresponding-Point Extraction from Weakly Textured Stereo Pairs. Mathematical Problems in Engineering No. 2014 (2014), pp.1-20.
https://search.emarefa.net/detail/BIM-1044374
American Medical Association (AMA)
Mao, Min& Hao, Kuangrong& Ding, Yongsheng. Self-Similarity Based Corresponding-Point Extraction from Weakly Textured Stereo Pairs. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-20.
https://search.emarefa.net/detail/BIM-1044374
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1044374