Title
Texture Super-Resolution in Multiview RGB-D Transmission
Abstract
Auto-stereoscopic displays allow viewers to experience 3D content by displaying multiple camera views. To reduce bandwidth requirements the multiview video plus depth (MVD) representation can be used, where only a subset of these camera views needs to be transmitted together with the depth maps. The display can then apply depth-image-based rendering techniques to reconstruct the missing views. In this work we propose further reduction in bandwidth through downsampling of the texture views before encoding and then apply a dictionary-based super-resolution method during the upsampling process at the receiver. The depth videos are still transmitted at full resolution. Multiview high efficiency video coding (MV-HEVC) is used to separately encode the texture and depth videos because of their different resolutions. The visual quality of the decoded and reconstructed content was evaluated through objective and subjective testing giving fair to good and poor to fair quality results for texture downsampling by two and four respectively.
Year
DOI
Venue
2018
10.1109/NGCAS.2018.8572164
2018 New Generation of CAS (NGCAS)
Keywords
Field
DocType
3D video,high efficiency video coding,multiview video plus depth,super-resolution
Computer vision,ENCODE,Computer science,Coding (social sciences),Bandwidth (signal processing),RGB color model,Artificial intelligence,Rendering (computer graphics),Upsampling,Image resolution,Encoding (memory)
Conference
ISBN
Citations 
PageRank 
978-1-5386-7682-0
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Julia Farrugia100.34
Carl James Debono23811.66