Real-time Video Quality Assessment Research Articles

Performance analysis of edge, fog and cloud computing paradigms for real-time video quality assessment and phishing detection

PurposeThe purpose of this paper is to perform a comparative analysis of the delay associated in running two real-time machine learning-based applications, namely, a video quality assessment (VQA) and a phishing detection application by using the edge, fog and cloud computing paradigms.Design/methodology/approachThe VQA algorithm was developed using Android Studio and run on a mobile phone for the edge paradigm. For the fog paradigm, it was hosted on a Java server and for the cloud paradigm on the IBM and Firebase clouds. The phishing detection algorithm was embedded into a browser extension for the edge paradigm. For the fog paradigm, it was hosted on a Node.js server and for the cloud paradigm on Firebase.FindingsFor the VQA algorithm, the edge paradigm had the highest response time while the cloud paradigm had the lowest, as the algorithm was computationally intensive. For the phishing detection algorithm, the edge paradigm had the lowest response time, and the cloud paradigm had the highest, as the algorithm had a low computational complexity. Since the determining factor for the response time was the latency, the edge paradigm provided the smallest delay as all processing were local.Research limitations/implicationsThe main limitation of this work is that the experiments were performed on a small scale due to time and budget constraints.Originality/valueA detailed analysis with real applications has been provided to show how the complexity of an application can determine the best computing paradigm on which it can be deployed.

Real-time Video Quality Assessment for Analog Television Based on Adaptive Fuzzy Membership Function Tuning

Real-time VQA (Video Quality Assessment) is an important part in the effort to build tracking antenna system especially for analog TV. In this case, VQA must work in real-time to assess the video clarity level. VQA assessment results are valuable information for the decision-making process. Thus, the antenna can rotate automatically looking for the ideal direction without user’s control. In addition, the video clarity level on the TV screen can reach optimum according to the user's wishes. The biggest challenge to VQA is, VQA must be able to assess the video clarity level according to the user’s visual perception. Therefore, in this study, the MOS-VQS (Mean Opinion Score-Video Quality Subjective) was used as a visual perception approach. In addition, Adaptive FIS (Fuzzy Inference System) with membership function tuning was implemented for decision making. This was conducted as an effort to build a reliable real-time VQA. The test results show that real-time VQA that has been built has a good performance. This is shown from the average accuracy percentage of the lowest assessment reached 77.2% and the highest reached 88.2%.

FPGA IMPLEMENTATION OF PROCEDURES FOR VIDEO QUALITY ASSESSMENT

Video resolutions used in a variety of media are constantly rising. While manufacturers struggle to perfect their screens, it is also important to ensure high quality of displayed image. Overall quality can be measured using Mean Opinion Score (MOS). Video quality can be aected by miscellaneous artifacts, appearing at every stage of video creation and transmission. In this paper, we present a solution to calculate four distinct video quality metrics that can be applied to a real-time video quality assessment system. Our assessment module is capable of processing 8K resolution in real time set at the level of 30 frames per second. The throughput of 2.19 GB/s surpasses the performance of pure software solutions. The module was created using a high-level language to concentrate on the architectural optimization.

Real-Time Video Quality Assessment Methods Based on No-Reference for Video Conference System

After a deep investigation on the performance measure of the video conference and the video quality assessment methods, the whole plan of video quality assessment (VQA) for video conference system is proposed. Without reference video source, a novel No-Reference (NR) VQA method based on both the coding layer information and the packet layer transmission performance is introduced. The experimental result shows that the proposed method can obtain the dependable score which close to the subjective assessment.

Joint assessment of Network- and Perceived-QoS in video delivery networks

Given the increasing number of IP streaming video customers, service providers are seeking an efficient way to monitor in real time the offered quality of service, as perceived by each end user. Since real-time video quality assessment via image processing algorithms is quite bandwidth- and processing-power-demanding, a feasible alternative could be to monitor the Network-level Quality of Service (NQoS) and associate it with the Perceived QoS (PQoS). This article presents a network-agnostic framework for the joint assessment of N- and P-QoS, with the aim of correlating these two parameters for a specific network and service configuration. This framework/architecture is implemented with open source software tools and is being demonstrated in an actual WiMAX streaming video distribution platform.