epipolar plane image rectification and flat surface detection in light field

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ID: 188024
2017
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Abstract
Flat surface detection is one of the most common geometry inferences in computer vision. In this paper we propose detecting printed photos from original scenes, which fully exploit angular information of light field and characteristics of the flat surface. Unlike previous methods, our method does not need a prior depth estimation. The algorithm rectifies the mess epipolar lines in the epipolar plane image (EPI). Then feature points are extracted from light field data and used to compute an energy ratio in the depth distribution of the scene. Based on the energy ratio, a feature vector is constructed and we obtain robust detection of flat surface. Apart from flat surface detection, the kernel rectification algorithm in our method can be expanded to inclined plane refocusing and continuous depth estimation for flat surface. Experiments on the public datasets and our collections have demonstrated the effectiveness of the proposed method.
Reference Key
si2017journalepipolar Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Lipeng Si;Hao Zhu;Qing Wang
Journal Molecular diversity
Year 2017
DOI
10.1155/2017/6142795
URL
http://dx.doi.org/10.1155/2017/6142795
Keywords
computer engineering computer hardware

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