scholarly journals A Model for Video Quality Assessment Considering Packet Loss for Broadcast Digital Television Coded in H.264

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Jose Joskowicz ◽  
Rafael Sotelo
Keyword(s):  
Packet Loss ◽  
Pearson Correlation ◽  
Video Quality ◽  
Ip Networks ◽  
High Variability ◽  
Digital Television ◽  
Packet Losses ◽  
Quality Estimation ◽  
Transport Stream ◽  
Proposed Model

This paper presents a model to predict video quality perceived by the broadcast digital television (DTV) viewer. We present how noise on DTV can introduce individual transport stream (TS) packet losses at the receiver. The type of these errors is different than the produced on IP networks. Different scenarios of TS packet loss are analyzed, including uniform and burst distributions. The results show that there is a high variability on the perceived quality for a given percentage of packet loss and type of error. This implies that there is practically no correlation between the type of error or the percentage of packets loss and the perceived degradation. A new metric is introduced, theweighted percentageof slice loss, which takes into account the affected slice type in each lost TS packet. We show that this metric is correlated with the video quality degradation. A novel parametric model for video quality estimation is proposed, designed, and verified based on the results of subjective tests in SD and HD. The results were compared to a standard model used in IP transmission scenarios. The proposed model improves Pearson Correlation and root mean square error between the subjective and the predicted MOS.

scholarly journals Packet Loss Measurement Based on Sampled Flow

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2149
Author(s):  
Haoliang Lan ◽  
Jie Xu ◽  
Qun Wang ◽  
Wei Ding
Keyword(s):  
Real Time ◽  
Packet Loss ◽  
Access Network ◽  
Packet Losses ◽  
Monitoring Point ◽  
Loss Measurement ◽  
Proposed Model ◽  
Comparison Results ◽  
Before And After ◽  
Network Boundary

This paper is devoted to further strengthening, in the current asymmetric information environment, the informed level of operators about network performance. Specifically, in view of the burst and perishability of a packet loss event, to better meet the real-time requirements of current high-speed backbone performance monitoring, a model for Packet Loss Measurement at the access network boundary Based on Sampled Flow (PLMBSF) is presented in this paper under the premise of both cost and real-time. The model overcomes problems such as the inability of previous estimation to distinguish between packet losses before and after the monitoring point, deployment difficulties and cooperative operation consistency. Drawing support from the Mathis equation and regression analysis, the measurement for packet losses before and after the monitoring point can be realized when using only the sampled flows generated by the access network boundary equipment. The comparison results with the trace-based passive packet loss measurement show that although the proposed model is easily affected by factors such as flow length, loss rate, sampling rate, the overall accuracy is still within the acceptable range. In addition, the proposed model PLMBSF, compared with the trace-based loss measurement is only different in the input data granularity. Therefore, PLMBSF and its advantages are also applicable to aggregated traffic.

Video quality estimation in wireless IP networks

2008 ◽  
Vol 4 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Fulvio Babich ◽  
Marco D'orlando ◽  
Francesca Vatta
Keyword(s):  
Video Quality ◽  
Ip Networks ◽  
Quality Estimation ◽  
Wireless Ip

A Video Quality Assessment Model Based on Edge Information

2012 ◽  
Vol 263-266 ◽  
pp. 218-222
Author(s):  
Xue Hui Wei ◽  
Meng Zhao
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Video Quality ◽  
Assessment Model ◽  
Video Quality Assessment ◽  
Multilinear Regression ◽  
Quality Estimation ◽  
Edge Information ◽  
Model Based ◽  
Proposed Model

Video quality assessment can be gotten by combination the distortion in the space area and the time area. As we all known that edge information is one of the most important features in image quality estimation. Based on the edge model in the perceived image quality estimation, we used it in the space and time area in the video, and get the edge information distorted model in space area and time area of the video. Using multilinear regression to combine the two models, we can get the video quality assessment model based on edge information. The proposed model only uses the edge information, and the consumption in both areas is small. After compared with other methods given by video quality estimation group, it’s found that our method is convenient and good at the 50 Hz video sequence of low bit rate(768kb/s -4.5 Mb/s).

scholarly journals Packet dispersion strategy evaluation from the perspective of packet loss pattern and VoIP quality

2016 ◽  
Vol 13 (1) ◽  
pp. 71-92 ◽  
Author(s):  
Nemanja Ninkovic ◽  
Slavko Gajin ◽  
Irini Reljin
Keyword(s):  
Packet Loss ◽  
Packet Losses ◽  
Quality Estimation ◽  
Loss Recovery ◽  
Network Testing ◽  
Strategy Evaluation ◽  
Practical Evaluation ◽  
Recovery Mechanisms ◽  
Individual Strategies

The appearance of burst packet losses and its devastating effect on Voice over IP (VoIP) service have imposed a requirement for the implementation of loss recovery mechanisms to address VoIP quality during periods when high packet loss is exhibited. Existing loss recovery mechanisms are dependent on end point capabilities, whereas Quality of service (QoS) routing protocols suffer from complexity and scalability issues. In this paper, we examine packet dispersion?s ability to address burst losses and provide a computational model, which is verified using real network testing. A study has been carried out to investigate the effect of different packet dispersion strategies on burst losses, which clearly shows dispersion?s qualitative superiority over single path routing. Furthermore, an analytical approach is proposed resulting in quality estimation obtained by individual strategies. Practical evaluation has shown that each strategy copes differently with various burst scenarios in order to maximize VoIP quality.

Enhanced context-aware recommendation using topic modeling and particle swarm optimization

2021 ◽  
pp. 1-16
Author(s):  
Ibtissem Gasmi ◽  
Mohamed Walid Azizi ◽  
Hassina Seridi-Bouchelaghem ◽  
Nabiha Azizi ◽  
Samir Brahim Belhaouari
Keyword(s):  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
State Of The Art ◽  
Weighting Function ◽  
Contextual Factors ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Pso Algorithm ◽  
Context Aware ◽  
Proposed Model

Context-Aware Recommender System (CARS) suggests more relevant services by adapting them to the user’s specific context situation. Nevertheless, the use of many contextual factors can increase data sparsity while few context parameters fail to introduce the contextual effects in recommendations. Moreover, several CARSs are based on similarity algorithms, such as cosine and Pearson correlation coefficients. These methods are not very effective in the sparse datasets. This paper presents a context-aware model to integrate contextual factors into prediction process when there are insufficient co-rated items. The proposed algorithm uses Latent Dirichlet Allocation (LDA) to learn the latent interests of users from the textual descriptions of items. Then, it integrates both the explicit contextual factors and their degree of importance in the prediction process by introducing a weighting function. Indeed, the PSO algorithm is employed to learn and optimize weights of these features. The results on the Movielens 1 M dataset show that the proposed model can achieve an F-measure of 45.51% with precision as 68.64%. Furthermore, the enhancement in MAE and RMSE can respectively reach 41.63% and 39.69% compared with the state-of-the-art techniques.

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.

scholarly journals Predicting the Energy Consumption of a Robot in an Exploration Task Using Optimized Neural Networks

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 920
Author(s):  
Liesle Caballero ◽  
Álvaro Perafan ◽  
Martha Rinaldy ◽  
Winston Percybrooks
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Mobile Robot ◽  
Energy Budget ◽  
Dynamic Models ◽  
Pearson Correlation ◽  
Experimental Conditions ◽  
Grid Map ◽  
Proposed Model ◽  
Exploration Task

This paper deals with the problem of determining a useful energy budget for a mobile robot in a given environment without having to carry out experimental measures for every possible exploration task. The proposed solution uses machine learning models trained on a subset of possible exploration tasks but able to make predictions on untested scenarios. Additionally, the proposed model does not use any kinematic or dynamic models of the robot, which are not always available. The method is based on a neural network with hyperparameter optimization to improve performance. Tabu List optimization strategy is used to determine the hyperparameter values (number of layers and number of neurons per layer) that minimize the percentage relative absolute error (%RAE) while maximize the Pearson correlation coefficient (R) between predicted data and actual data measured under a number of experimental conditions. Once the optimized artificial neural network is trained, it can be used to predict the performance of an exploration algorithm on arbitrary variations of a grid map scenario. Based on such prediction, it is possible to know the energy needed for the robot to complete the exploration task. A total of 128 tests were carried out using a robot executing two exploration algorithms in a grid map with the objective of locating a target whose location is not known a priori by the robot. The experimental energy consumption was measured and compared with the prediction of our model. A success rate of 96.093% was obtained, measured as the percentage of tests where the energy budget suggested by the model was enough to actually carry out the task when compared to the actual energy consumed in the test, suggesting that the proposed model could be useful for energy budgeting in actual mobile robot applications.

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