TY - JOUR
T1 - Epipolar Plane Image Rectification and Flat Surface Detection in Light Field
AU - Si, Lipeng
AU - Zhu, Hao
AU - Wang, Qing
N1 - Publisher Copyright:
© 2017 Lipeng Si et al.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85030781212&partnerID=8YFLogxK
U2 - 10.1155/2017/6142795
DO - 10.1155/2017/6142795
M3 - 文章
AN - SCOPUS:85030781212
SN - 2090-0147
VL - 2017
JO - Journal of Electrical and Computer Engineering
JF - Journal of Electrical and Computer Engineering
M1 - 6142795
ER -