Paper Info
Title
An occlusion compensation model for improving the reconstruction quality of light field
Abstract
Occlusion lack compensation (OLC) is a multi-plexing gain optimization data acquisition and novel views rendering strategy for light field rendering (LFR). While the achieved OLC is much higher than previously thought possible, the improvement comes at the cost of requiring more scene information. This can capture more detailed scene information, including geometric information, texture information and depth information, by learning and training methods. In this paper, we develop an occlusion compensation (OCC) model based on restricted boltzmann machine (RBM) to compensate for lack scene information caused by occlusion. We show that occlusion will cause the lack of captured scene information, which will lead to the decline of view rendering quality. The OCC model can estimate and compensate the lack information of occlusion edge by learning. We present experimental results to demonstrate the performance of OCC model with analog training, verify our theoretical analysis, and extend our conclusions on optimal rendering quality of light field.
Year
DOI
Venue
2020
10.1109/MMSP48831.2020.9287094
2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)
Keywords
DocType
ISSN
Occlusion,occlusion compensation model,capturing information,light field rendering
Conference
2163-3517
ISBN
Citations 
PageRank 
978-1-7281-9323-6
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Jinjie Bi100.34
Weiyan Chen262.79
Changjian Zhu302.37
Hong Zhang427626.98
Min Tan52342201.12