3D Video Encoding

2012 ◽  
pp. 315-341 ◽  
Author(s):  
Takashi Matsuyama ◽  
Shohei Nobuhara ◽  
Takeshi Takai ◽  
Tony Tung
Keyword(s):  
3D Video ◽  
Video Encoding

scholarly journals Video Traffic Characteristics of Modern Encoding Standards: H.264/AVC with SVC and MVC Extensions and H.265/HEVC

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Patrick Seeling ◽  
Martin Reisslein
Keyword(s):  
Video Coding ◽  
Communication Networks ◽  
Single Layer ◽  
3D Video ◽  
Video Encoding ◽  
Multimedia Communications ◽  
Statistical Multiplexing ◽  
Video Traffic ◽  
Traffic Characteristics ◽  
Coding Standards

Video encoding for multimedia services over communication networks has significantly advanced in recent years with the development of the highly efficient and flexible H.264/AVC video coding standard and its SVC extension. The emerging H.265/HEVC video coding standard as well as 3D video coding further advance video coding for multimedia communications. This paper first gives an overview of these new video coding standards and then examines their implications for multimedia communications by studying the traffic characteristics of long videos encoded with the new coding standards. We review video coding advances from MPEG-2 and MPEG-4 Part 2 to H.264/AVC and its SVC and MVC extensions as well as H.265/HEVC. For single-layer (nonscalable) video, we compare H.265/HEVC and H.264/AVC in terms of video traffic and statistical multiplexing characteristics. Our study is the first to examine the H.265/HEVC traffic variability for long videos. We also illustrate the video traffic characteristics and statistical multiplexing of scalable video encoded with the SVC extension of H.264/AVC as well as 3D video encoded with the MVC extension of H.264/AVC.

Invariant shape descriptor for 3D video encoding

2014 ◽  
Vol 31 (3) ◽  
pp. 311-324 ◽  
Author(s):  
Tony Tung ◽  
Takashi Matsuyama
Keyword(s):  
Shape Descriptor ◽  
3D Video ◽  
Video Encoding ◽  
Invariant Shape

A Whole Rate-Distortion Optimize Pronounce Based on Wireless Sensor Network

2013 ◽  
Vol 756-759 ◽  
pp. 890-894 ◽  
Author(s):  
Qing Sheng Yu ◽  
Jian Zhang ◽  
Jin Xiang Peng
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Estimation Method ◽  
Rate Distortion ◽  
Video Encoding ◽  
Mode Decision ◽  
Wireless Sensor ◽  
Block Basis ◽  
Decision Scheme ◽  
Macro Block

Based on the Joint Video Team (JVT) of the ITU-T Video Coding Experts Group VC EG and the IS O/IEC Moving Picture Experts Group MPEG, an RD optimal Macro Block mode decision scheme for Internet error channel streaming is introduced. The scheme employs the luminance Rate Distortion (RD) optimal mode decision scheme so as to take the effects of video encoding distortion and the channel error propagation to get higher error robustness for error transmission. Based on the Wireless Sensor Network, this paper analyzes the data distortion problem when transmitting H.264 coded video stream over error-prone channel. And the authors also have discussed a widely accepted technique that introduces more intra-coded information on macro block basis. Additionally, this paper introduces a simple loss and multiplication factor estimation method, the rate-distortion optimized assessing strategy over the whole situation.

Development of 3D video and 3D data services for T-DMB

2008 ◽  
Author(s):  
Kugjin Yun ◽  
Hyun Lee ◽  
Namho Hur ◽  
Jinwoong Kim
Keyword(s):  
3D Video ◽  
Data Services ◽  
3D Data

scholarly journals Content Dependent Representation Selection Model for Systems Based on MPEG DASH

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1843
Author(s):  
Jelena Vlaović ◽  
Snježana Rimac-Drlje ◽  
Drago Žagar
Keyword(s):  
Mathematical Model ◽  
Spatial Information ◽  
Relevant Literature ◽  
Video Quality ◽  
Similarity Index ◽  
Video Encoding ◽  
Adaptation Algorithm ◽  
Subjective Testing ◽  
Proposed Model ◽  
The Mathematical Model

A standard called MPEG Dynamic Adaptive Streaming over HTTP (MPEG DASH) ensures the interoperability between different streaming services and the highest possible video quality in changing network conditions. The solutions described in the available literature that focus on video segmentation are mostly proprietary, use a high amount of computational power, lack the methodology, model notation, information needed for reproduction, or do not consider the spatial and temporal activity of video sequences. This paper presents a new model for selecting optimal parameters and number of representations for video encoding and segmentation, based on a measure of the spatial and temporal activity of the video content. The model was developed for the H.264 encoder, using Structural Similarity Index Measure (SSIM) objective metrics as well as Spatial Information (SI) and Temporal Information (TI) as measures of video spatial and temporal activity. The methodology that we used to develop the mathematical model is also presented in detail so that it can be applied to adapt the mathematical model to another type of an encoder or a set of encoding parameters. The efficiency of the segmentation made by the proposed model was tested using the Basic Adaptation algorithm (BAA) and Segment Aware Rate Adaptation (SARA) algorithm as well as two different network scenarios. In comparison to the segmentation available in the relevant literature, the segmentation based on the proposed model obtains better SSIM values in 92% of cases and subjective testing showed that it achieves better results in 83.3% of cases.

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