학술논문

Using Bayesian classifiers for low complexity multiview H.264/AVC and HEVC hybrid architecture
Document Type
Conference
Source
2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP) Machine Learning for Signal Processing (MLSP), 2015 IEEE 25th International Workshop on. :1-6 Sep, 2015
Subject
Computing and Processing
Signal Processing and Analysis
Video coding
Encoding
Three-dimensional displays
Computer architecture
Complexity theory
Standards
Streaming media
H.264/AVC
HEVC
Multiview Hybrid Coding
CTU Splitting
Language
ISSN
1551-2541
2378-928X
Abstract
In order to enable a system which offers compatibility with currently existing H.264/AVC based systems, 3D functionality, and a low overall bitrate, a multiview H.264/HEVC hybrid architecture was proposed in the context of 3D applications and standardization. This paper presents an algorithm to reduce the complexity of this multiview hybrid architecture by reducing the encoding complexity of the HEVC side views. The proposed technique exploits the information gathered in the center view of the H.264/AVC encoder of this hybrid mul-tiview architecture to make decisions on Coding Units splitting in HEVC side views using a Naïve-Bayes probabilistic classifier. Thus, the proposal is quite novel since no similar works has been found in the literature and it exploits a new characteristic of the multiview HEVC streams which was not present in previous standards. Experimental results show that the proposed algorithm can achieve a good tradeoff between coding efficiency and complexity.