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2019 | OriginalPaper | Chapter

Anti-occlusion Light-Field Optical Flow Estimation Using Light-Field Super-Pixels

Authors : Hao Zhu, Xiaoming Sun, Qi Zhang, Qing Wang, Antonio Robles-Kelly, Hongdong Li

Published in: Computer Vision – ACCV 2018 Workshops

Publisher: Springer International Publishing

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Abstract

Optical flow estimation is one of the most important problem in community. However, current methods still can not provide reliable results in occlusion boundary areas. Light field cameras provide hundred of views in a single shot, so the ambiguity can be better analysed using other views. In this paper, we present a novel method for anti-occlusion optical flow estimation in a dynamic light field. We first model the light field superpixel (LFSP) as a slanted plane in 3D. Then the motion of the occluded pixels in central view slice can be optimized by the un-occluded pixels in other views. Thus the optical flow in occlusion boundary areas can be well computed. Experimental results on both synthetic and real light fields demonstrate the advantages over state-of-the-arts and the performance on 4D optical flow computation.

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Title: Anti-occlusion Light-Field Optical Flow Estimation Using Light-Field Super-Pixels
Authors: Hao Zhu
Xiaoming Sun
Qi Zhang
Qing Wang
Antonio Robles-Kelly
Hongdong Li
Publisher: Springer International Publishing
Book: Computer Vision – ACCV 2018 Workshops
Print ISBN: 978-3-030-21073-1

Electronic ISBN: 978-3-030-21074-8

Copyright Year: 2019
DOI: https://doi.org/10.1007/978-3-030-21074-8_1

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