2020 IEEE International Conference on Image Processing (ICIP) 2020
DOI: 10.1109/icip40778.2020.9191118
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A Spatio-Angular Binary Descriptor For Fast Light Field Inter View Matching

Abstract: Light fields are able to capture light rays from a scene arriving at different angles, effectively creating multiple perspective views of the same scene. Thus, one of the flagship applications of light fields is to estimate the captured scene geometry, which can notably be achieved by establishing correspondences between the perspective views, usually in the form of a disparity map. Such correspondence estimation has been a long standing research topic in computer vision, with application to stereo vision or o… Show more

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Cited by 2 publications
(3 citation statements)
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“…To facilitate feature matching between multiple views, Alain et al [17] propose an improved feature description for binarized features in the light field spatial-angular domain. Liu et al [17] propose a focused all-optical camera feature detection based on a center-projected stereo focus stack.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…To facilitate feature matching between multiple views, Alain et al [17] propose an improved feature description for binarized features in the light field spatial-angular domain. Liu et al [17] propose a focused all-optical camera feature detection based on a center-projected stereo focus stack.…”
Section: Introductionmentioning
confidence: 99%
“…To facilitate feature matching between multiple views, Alain et al [17] propose an improved feature description for binarized features in the light field spatial-angular domain. Liu et al [17] propose a focused all-optical camera feature detection based on a center-projected stereo focus stack. The above light field feature extractions and matchings outperform the classic 2D image feature algorithms in terms of precision and robustness, and show a great potential to solve the problem of feature matching ambiguity.…”
Section: Introductionmentioning
confidence: 99%
“…Ji et al [26] propose a LF directional gradient histogram (LFHoG) feature to achieve high precision live face detection, while a LF local binary patterns (LFLBP) is introduced in [27], which enhances the LF based face recognition. The authors in [28] propose a solution of accurate and fast disparity estimation by introducing a binary descriptor, which exploits the light field gradient over both the spatial and the angular dimensions.…”
Section: Introductionmentioning
confidence: 99%