Influence of textures on the robustness of the depth estimation algorithm for light field

2018 ◽  
Author(s):  
Yao Hu ◽  
Shuo Peng ◽  
Qun Hao
Keyword(s):  
Light Field ◽  
Depth Estimation ◽  
Estimation Algorithm

scholarly journals Three-Dimensional Reconstruction of Light Field Based on Phase Similarity

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7734
Author(s):  
Wei Feng ◽  
Junhui Gao ◽  
Tong Qu ◽  
Shiqi Zhou ◽  
Daxing Zhao
Keyword(s):  
3D Reconstruction ◽  
Light Field ◽  
Three Dimensional ◽  
Ground Truth ◽  
Depth Estimation ◽  
Estimation Algorithm ◽  
Morphological Processing ◽  
Disparity Estimation ◽  
Reconstruction Method ◽  
Disparity Map

Light field imaging plays an increasingly important role in the field of three-dimensional (3D) reconstruction because of its ability to quickly obtain four-dimensional information (angle and space) of the scene. In this paper, a 3D reconstruction method of light field based on phase similarity is proposed to increase the accuracy of depth estimation and the scope of applicability of epipolar plane image (EPI). The calibration method of the light field camera was used to obtain the relationship between disparity and depth, and the projector calibration was removed to make the experimental procedure more flexible. Then, the disparity estimation algorithm based on phase similarity was designed to effectively improve the reliability and accuracy of disparity calculation, in which the phase information was used instead of the structure tensor, and the morphological processing method was used to denoise and optimize the disparity map. Finally, 3D reconstruction of the light field was realized by combining disparity information with the calibrated relationship. The experimental results showed that the reconstruction standard deviation of the two objects was 0.3179 mm and 0.3865 mm compared with the ground truth of the measured objects, respectively. Compared with the traditional EPI method, our method can not only make EPI perform well in a single scene or blurred texture situations but also maintain good reconstruction accuracy.

Depth Estimation with Occlusion Modeling Using Light-Field Cameras

2016 ◽  
Vol 38 (11) ◽  
pp. 2170-2181 ◽  
Author(s):  
Ting-Chun Wang ◽  
Alexei A. Efros ◽  
Ravi Ramamoorthi
Keyword(s):  
Light Field ◽  
Depth Estimation

Self-Supervised Light Field Depth Estimation Using Epipolar Plane Images

2021 ◽  
Author(s):  
Kunyuan Li ◽  
Jun Zhang ◽  
Jun Gao ◽  
Meibin Qi
Keyword(s):  
Light Field ◽  
Depth Estimation

scholarly journals Efficient Light Field Images Compression Method Based on Depth Estimation and Optimization

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 48984-48993 ◽  
Author(s):  
Xinpeng Huang ◽  
Ping An ◽  
Liquan Shen ◽  
Ran Ma
Keyword(s):  
Light Field ◽  
Depth Estimation ◽  
Compression Method
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