Epipolar Plane Image Rectification and Flat Surface Detection in Light Field
Joint Authors
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-19
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
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.
American Psychological Association (APA)
Si, Lipeng& Zhu, Hao& Wang, Qing. 2017. Epipolar Plane Image Rectification and Flat Surface Detection in Light Field. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1175337
Modern Language Association (MLA)
Si, Lipeng…[et al.]. Epipolar Plane Image Rectification and Flat Surface Detection in Light Field. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-9.
https://search.emarefa.net/detail/BIM-1175337
American Medical Association (AMA)
Si, Lipeng& Zhu, Hao& Wang, Qing. Epipolar Plane Image Rectification and Flat Surface Detection in Light Field. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-9.
https://search.emarefa.net/detail/BIM-1175337
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175337