Title
Light-Field Depth Estimation via Epipolar Plane Image Analysis and Locally Linear Embedding
Abstract
In this paper, we propose a novel method for 4D light-field (LF) depth estimation exploiting the special linear structure of an epipolar plane image (EPI) and locally linear embedding (LLE). Without high computational complexity, depth maps are locally estimated by locating the optimal slope of each line segmentation on the EPIs, which are projected by the corresponding scene points. For each pixel to be processed, we build and then minimize the matching cost that aggregates the intensity pixel value, gradient pixel value, spatial consistency, as well as reliability measure to select the optimal slope from a predefined set of directions. Next, a subangle estimation method is proposed to further refine the obtained optimal slope of each pixel. Furthermore, based on a local reliability measure, all the pixels are classified into reliable and unreliable pixels. For the unreliable pixels, LLE is employed to propagate the missing pixels by the reliable pixels based on the assumption of manifold preserving property maintained by natural images. We demonstrate the effectiveness of our approach on a number of synthetic LF examples and real-world LF data sets, and show that our experimental results can achieve higher performance than the typical and recent state-of-the-art LF stereo matching methods. © 2017 IEEE.
Year
DOI
Venue
2017
10.1109/TCSVT.2016.2555778
IEEE Transactions on Circuits and Systems for Video Technology
Keywords
Field
DocType
Depth estimation,Epipolar plane image (EPI),Light field (LF),Locally linear embedding (LLE)
Iterative reconstruction,Computer vision,Data set,Embedding,Epipolar geometry,Segmentation,Computer science,Artificial intelligence,Pixel,Computational complexity theory,Pixel connectivity
Journal
Volume
Issue
ISSN
27
4
10518215
Citations 
PageRank 
References 
5
0.44
13
Authors
8
Name
Order
Citations
PageRank
Zhang Y145950.31
Lv Huijin250.44
Yebin Liu368849.05
Wang H47129.35
Wang Xingzheng573.18
Huang Qian6113.59
Xiang Xinguang7111.54
Qionghai Dai83904215.66