Video Quality Evaluation for H.264 Video Streaming over Wireless Networks

2013 ◽  
Vol 760-762 ◽  
pp. 639-642
Author(s):  
Li Qiang Liu ◽  
Yue Bing Wang ◽  
Quan Feng Yan
Keyword(s):  
Wireless Networks ◽  
Wireless Network ◽  
Video Transmission ◽  
Rapid Development ◽  
Video Quality ◽  
Video Encoding ◽  
Network Bandwidth ◽  
Transmission Quality ◽  
Routing Technology

With the rapid development of computer technology and wireless network communication technology, video encoding technology will be more and more widely applied in the limited resources of the wireless network. Due to the large amount of data of the video transmission , transmission quality of transmit video on the wireless network are varied with different compression parameters, network parameters and network conditions. Simulation results show that the transmission of video over wireless networks, must be based on the current network conditions, choosing the suitable GOP length and quantitative parameters to get the high image quality. In specific applications, network topology, network bandwidth, routing technology and transmission of packet segmentation scheme and other factors will affect the quality of service for video services.

A Framework for Evaluation of Video Quality of Service in Wireless Networks

2017 ◽  
pp. 1-29
Author(s):  
Dharm Singh ◽  
Lal Chand Bishnoi
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
Video Transmission ◽  
Video Quality ◽  
Measuring Technique ◽  
New Techniques ◽  
Ieee 802.11N ◽  
Transmission Quality ◽  
Video Transmission Quality

Today's IEEE 802.11n WLAN are capable of delivering the essential bandwidth for video by using MPEG-4 or H.264 codec compression. However, 802.11n devices are popular for delivering wireless video transmission. Even though there are some challenges for these devices specifically severe network congestion that degrade the quality of video transmission. For assessing the video transmission quality during a simulation on 802.11n WLAN technology, we extended a framework and toolset (802.11nMyEvalVid) which can be used to measures the QoS constraints in wireless networks, such as throughput, delays, and end-to-end delay. However, it also supports PSNR, which is a received video quality measuring technique based on a comparison of frame-by-frame. This chapter focused on a framework 802.11nMyEvalVid that can be used for research and evaluating new techniques for MAC-layer optimizations for simulating MPEG-4, H.264/AVC and H.264/SVC video over 802.11n WLAN in a more efficient and reliable way.

Study on Adaptive QoS Solution of Real-Time Video Stream in Wireless Network

2012 ◽  
Vol 532-533 ◽  
pp. 1124-1129
Author(s):  
Xiao Yun Xiong ◽  
Bing Wang ◽  
De Xing Wang
Keyword(s):  
Wireless Networks ◽  
Real Time ◽  
Wireless Network ◽  
Video Transmission ◽  
Rapid Development ◽  
Video Stream ◽  
Link State ◽  
Multiple Qos ◽  
Adaptive Qos

With the rapid development of wireless network technology, wireless networks have been widely used in many fields due to the flexibility of wireless access. However, in the field of video transmission, because the link state is instability and the transmission is easily interfered in wireless networks, the quality of video transmission is affected badly. In fading and shadowing channels, some users can’t watch the video normally. This paper provides an adaptive QoS solution of real-time video stream in wireless network, by adding a relay server it can provide multicast or unicast video stream satisfying multiple QoS for users with different network state. This solution has been successfully applied in Qingdao Public safety emergency video surveillance system.

Machine Learning-Based Subjective Quality Estimation for Video Streaming Over Wireless Networks

2019 ◽  
pp. 235-254
Author(s):  
Monalisa Ghosh ◽  
Chetna Singhal
Keyword(s):  
Machine Learning ◽  
Wireless Networks ◽  
Video Streaming ◽  
Video Transmission ◽  
Video Quality ◽  
Subjective Quality ◽  
Perceptual Quality ◽  
Support Vector ◽  
Machine Learning Model

Video streaming services top the internet traffic surging forward a competitive environment to impart best quality of experience (QoE) to the users. The standard codecs utilized in video transmission systems eliminate the spatiotemporal redundancies in order to decrease the bandwidth requirement. This may adversely affect the perceptual quality of videos. To rate a video quality both subjective and objective parameters can be used. So, it is essential to construct frameworks which will measure integrity of video just like humans. This chapter focuses on application of machine learning to evaluate the QoE without requiring human efforts with higher accuracy of 86% and 91% employing the linear and support vector regression respectively. Machine learning model is developed to forecast the subjective quality of H.264 videos obtained after streaming through wireless networks from the subjective scores.

Communication Performance Research for Online Video over Wireless Multimedia Network

2013 ◽  
Vol 760-762 ◽  
pp. 643-646
Author(s):  
Yue Bin Wang ◽  
Li Qiang Liu ◽  
Quan Feng Yan
Keyword(s):  
Wireless Network ◽  
Video Transmission ◽  
Limited Resources ◽  
Online Video ◽  
Wireless Multimedia ◽  
Communication Performance ◽  
Loss Probabilities ◽  
Transmission Quality ◽  
Performance Research

This paper analyzed the communication performance to implement video coding and transmission in the limited resources of wireless network. Meanwhile, the effect of GOP, quantification and loss probabilities to transmission quality in multimedia communication is discussed, and the correlation between those relevant parameters and transmission quality of multimedia video is analyzed by simulation. The simulation results show that the transmission quality of multimedia video in wireless network varies with the compression parameters, network parameters, and network conditions. Thus, video transmission over wireless network, it should consider the network conditions, as well as appropriate length of the GOP and quantification parameters for better reconstructed images.

scholarly journals Video Transmission In Wireless Multihop Networks

2019 ◽  
Vol 8 (6) ◽  
pp. 3562-3565
Keyword(s):  
Wireless Networks ◽  
Wireless Network ◽  
Video Streaming ◽  
Video Transmission ◽  
Packet Scheduling ◽  
Video Quality ◽  
Video Communications ◽  
Wireless Data ◽  
Wireless Data Transmission ◽  
Wide Range

Multi hop wireless networks are being deployed in many video streaming applications because they have several potential features for next generation wireless communications. Though optimal encoding techniques offers significant quality retention in video transmission still it is insufficient to overcome the challenges ahead over wireless network transmission. In order to support wide range video communications in an efficient way certain Quality of service has to be retained in multi hop wireless network. To address this issue, this paper investigates several encoding and routing protocols video delivery over multi hop wireless networks. Specifically, we first investigate several encoding framework for videos and wireless data transmission over WMNs through individual paths; we then investigate the challenges ahead to formulate resistant routing model for least possible video quality dictions which incorporate channel status as well as the encoder properties over video characteristics. In this framework, routing techniques which can maximally used to achieve good video traffic with improved system performance. However, video streaming also have very stringent delay requirements, which makes it difficult to find optimal routes with the least possible distortions. To address this problem, we investigate several enhanced version of packet scheduling techniques for video communications over multi path multi hob multi user wireless network environment.

Demand of Wireless Network and Security in Current Research

2015 ◽  
Vol 14 (6) ◽  
pp. 5809-5813
Author(s):  
Abhishek Prabhakar ◽  
Amod Tiwari ◽  
Vinay Kumar Pathak
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
Wireless Network ◽  
Network Performance ◽  
Wireless Security ◽  
Human Intervention ◽  
Unauthorized Access ◽  
Quality Of Service Parameters ◽  
Wireless Infrastructure

Wireless security is the prevention of unauthorized access to computers using wireless networks .The trends in wireless networks over the last few years is same as growth of internet. Wireless networks have reduced the human intervention for accessing data at various sites .It is achieved by replacing wired infrastructure with wireless infrastructure. Some of the key challenges in wireless networks are Signal weakening, movement, increase data rate, minimizing size and cost, security of user and QoS (Quality of service) parameters... The goal of this paper is to minimize challenges that are in way of our understanding of wireless network and wireless network performance.

An Improved Error Concealment Based on Redundant Motion Vector Information

2012 ◽  
Vol 532-533 ◽  
pp. 1219-1224
Author(s):  
Hong Tao Deng
Keyword(s):  
Video Transmission ◽  
Error Concealment ◽  
Video Quality ◽  
Motion Vector ◽  
Compressed Video ◽  
Vector Information ◽  
Vector Estimation ◽  
Channel Errors ◽  
Bit Stream

During video transmission over error prone network, compressed video bit-stream is sensitive to channel errors that may degrade the decoded pictures severely. In order to solve this problem, error concealment technique is a useful post-processing tool for recovering the lost information. In these methods, how to estimate the lost motion vector correctly is important for the quality of decoded picture. In order to recover the lost motion vector, an Decoder Motion Vector Estimation (DMVE) criterion was proposed and have well effect for recover the lost blocks. In this paper, we propose an improved error concealment method based on DMVE, which exploits the accurate motion vector by using redundant motion vector information. The experimental results with an H.264 codec show that our method improves both subjective and objective decoder reconstructed video quality, especially for sequences of drastic motion.

Quality of Experience vs. QoS in Video Transmission

2010 ◽  
pp. 352-376 ◽  
Author(s):  
André F. Marquet ◽  
Jânio M. Monteiro ◽  
Nuno J. Martins ◽  
Mario S. Nunes
Keyword(s):  
Communication Networks ◽  
Video Transmission ◽  
Quality Of Experience ◽  
Video Quality ◽  
Subjective Assessment ◽  
Ip Networks ◽  
Point Of View ◽  
Qos Parameters ◽  
Quality Video

In legacy television services, user centric metrics have been used for more than twenty years to evaluate video quality. These subjective assessment metrics are usually obtained using a panel of human evaluators in standard defined methods to measure the impairments caused by a diversity of factors of the Human Visual System (HVS), constituting what is also called Quality of Experience (QoE) metrics. As video services move to IP networks, the supporting distribution platforms and the type of receiving terminals is getting more heterogeneous, when compared with classical video distributions. The flexibility introduced by these new architectures is, at the same time, enabling an increment of the transmitted video quality to higher definitions and is supporting the transmission of video to lower capability terminals, like mobile terminals. In IP Networks, while Quality of Service (QoS) metrics have been consistently used for evaluating the quality of a transmission and provide an objective way to measure the reliability of communication networks for various purposes, QoE metrics are emerging as a solution to address the limitations of conventional QoS measuring when evaluating quality from the service and user point of view. In terms of media, compressed video usually constitutes a very interdependent structure degrading in a non-graceful manner when exposed to Binary Erasure Channels (BEC), like the Internet or wireless networks. Accordingly, not only the type of encoder and its major encoding parameters (e.g. transmission rate, image definition or frame rate) contribute to the quality of a received video, but also QoS parameters are usually a cause for different types of decoding artifacts. As a result of this, several worldwide standard entities have been evaluating new metrics for the subjective assessment of video transmission over IP networks. In this chapter we are especially interested in explaining some of the best practices available to monitor, evaluate and assure good levels of QoE in packet oriented networks for rich media applications like high quality video streaming. For such applications, service requirements are relatively loose or difficult to quantify and therefore specific techniques have to be clearly understood and evaluated. By the mid of the chapter the reader should have understood why even networks with excellent QoS parameters might have QoE issues, as QoE is a systemic approach that does not relate solely to QoS but to the ensemble of components composing the communication system.

Applied Research of Assessment Methods on Video Quality

2012 ◽  
Vol 262 ◽  
pp. 157-162
Author(s):  
Chong Gu ◽  
Zhan Jun Si
Keyword(s):  
Video Processing ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Rapid Development ◽  
Video Quality ◽  
Objective Evaluation ◽  
Video Data ◽  
Assessment System ◽  
Video Encoding ◽  
High Definition

With the rapid development of modern video technology, the range of video applications is increasing, such as online video conferencing, online classroom, online medical, etc. However, due to the quantity of video data is large, video has to be compressed and encoded appropriately, but the encoding process may cause some distortions on video quality. Therefore, how to evaluate the video quality efficiently and accurately is essential in the fields of video processing, video quality monitoring and multimedia video applications. In this article, subjective, and comprehensive evaluation method of video quality were introduced, a video quality assessment system was completed, four ITU recommended videos were encoded and evaluated by Degradation Category Rating (DCR) and Structural Similarity (SSIM) methods using five different formats. After that, comprehensive evaluations with weights were applied. Results show that data of all three evaluations have good consistency; H.264 is the best encoding method, followed by Xvid and wmv8; the higher the encoding bit rate is, the better the evaluations are, but comparing to 1000kbps, the subjective and objective evaluation scores of 1400kbps couldn’t improve obviously. The whole process could also evaluate new encodings methods, and is applicable for high-definition video, finally plays a significant role in promoting the video quality evaluation and video encoding.

Real-Time Bus Video Monitoring System Based on 3G Network

2013 ◽  
Vol 380-384 ◽  
pp. 790-793
Author(s):  
Min Feng ◽  
Jie Sun ◽  
Yin Yang Zhang
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Video Transmission ◽  
Video Data ◽  
Video Monitoring ◽  
Network Bandwidth ◽  
Real Time Traffic ◽  
3G Network ◽  
Transmission Quality ◽  
Video Transmission Quality

According to some bottleneck problems of the communication network bandwidth in wireless video transmission, a design scheme of real-time traffic video monitoring system based on 3G network is put forward in this paper. The design of hardware and the software realization of the system process are mainly introduced. TMS320DM8168 is selected to build the hardware platform in this system. H.264 video encoder is integrated internally. The real-time transmission of video data is sent to the remote monitoring center through the 3G network to improve the video transmission quality. The system meets the requirements of video transmission applied in automobiles.

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