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Improving the prediction accuracy of video quality metrics

Christian Keimel, Tobias Oelbaum, Klaus Diepold
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
To improve the prediction accuracy of visual quality metrics for video we propose two simple steps: temporal pooling in order to gain a set of parameters from one measured feature and a correction step  ...  Secondly, we exploit the almost linear relationship between the output of a quality metric and the subjectively perceived visual quality for individual video sequences.  ...  It improves the prediction accuracy by estimating the relationship between the output of the metric and the perceived visual quality for the video.  ... 
doi:10.1109/icassp.2010.5496299 dblp:conf/icassp/KeimelOD10 fatcat:54q4z75bdvc5xky5oxy2c4a3cq

A machine learning based approach for frame work of objective video quality assessment system

2021 International Journal of Advanced Trends in Computer Science and Engineering  
Hence, more video quality metrics have to be used for the quantification of video quality. So, hybrid quality metrics are required for quantification of video quality.  ...  Video quality assessment aims to predict viewer's opinion through objective means. A single videoquality metricis not sufficient to predict and quantify the test video.  ...  For the analysis of video quality scores and to predict the video quality score, we have used data mining based approach.  ... 
doi:10.30534/ijatcse/2021/481012021 fatcat:i6kdfrmkvjajfnhds2ac5ih7dy

Predicting QoE Factors with Machine Learning

Vladislav Vasilev, Jeremie Leguay, Stefano Paris, Lorenzo Maggi, Merouane Debbah
2018 2018 IEEE International Conference on Communications (ICC)  
Classic network control techniques have as sole objective the fulfillment of Quality-of-Service (QoS) metrics, being quantitative and network-centric.  ...  Nowadays, the research community envisions a paradigm shift that will put the emphasis on Quality of Experience (QoE) metrics, which relate directly to the user satisfaction.  ...  We show that the use of predicted hidden variables as features can indeed improve accuracy for re-buffering events.  ... 
doi:10.1109/icc.2018.8422609 dblp:conf/icc/VasilevLPMD18 fatcat:l4amqzag25gkxnz75bvf4ukj5i

Developing a predictive model of quality of experience for internet video

Athula Balachandran, Vyas Sekar, Aditya Akella, Srinivasan Seshan, Ion Stoica, Hui Zhang
2013 Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM - SIGCOMM '13  
The goal of this paper is to develop a predictive model of Internet video QoE.  ...  Improving users' quality of experience (QoE) is crucial for sustaining the advertisement and subscription based revenue models that enable the growth of Internet video.  ...  Acknowledgements We thank our shepherd Jon Crowcroft and the anonymous reviewers for their feedback that helped improve the paper.  ... 
doi:10.1145/2486001.2486025 dblp:conf/sigcomm/BalachandranSASSZ13 fatcat:vax2wyrpiffgndlyhlmi3i3amm

Developing a predictive model of quality of experience for internet video

Athula Balachandran, Vyas Sekar, Aditya Akella, Srinivasan Seshan, Ion Stoica, Hui Zhang
2013 Computer communication review  
The goal of this paper is to develop a predictive model of Internet video QoE.  ...  Improving users' quality of experience (QoE) is crucial for sustaining the advertisement and subscription based revenue models that enable the growth of Internet video.  ...  Acknowledgements We thank our shepherd Jon Crowcroft and the anonymous reviewers for their feedback that helped improve the paper.  ... 
doi:10.1145/2534169.2486025 fatcat:etnpbcczejebvooxzvglmeqmwi

A no-reference machine learning based video quality predictor

Muhammad Shahid, Andreas Rossholm, Benny Lovstrom
2013 2013 Fifth International Workshop on Quality of Multimedia Experience (QoMEX)  
Several full reference quality metrics are predicted using the proposed model with reasonably good levels of accuracy, monotonicity and consistency.  ...  The growing need of quick and online estimation of video quality necessitates the study of new frontiers in the area of no-reference visual quality assessment.  ...  An improvement of this approach was presented in [6] where the required number of parameters have been reduced for computational efficiency and the prediction accuracy has been improved by the virtue  ... 
doi:10.1109/qomex.2013.6603233 dblp:conf/qomex/ShahidRL13 fatcat:rsfqszwk6rdezbmmymsgdcb5zm

Extending video quality metrics to the temporal dimension with 2D-PCR

Christian Keimel, Martin Rothbucher, Klaus Diepold, Susan P. Farnand, Frans Gaykema
2011 Image Quality and System Performance VIII  
The aim of any video quality metric is to deliver a quality prediction similar to the video quality perceived by human observers.  ...  Finally, we will show that the direct inclusion of the temporal dimension of video into the model building improves the overall prediction accuracy of the visual quality significantly.  ...  domain of video in the model building step will improve the quality prediction abilities of metrics.  ... 
doi:10.1117/12.872406 fatcat:kth36v67nrcbrcukzw3zjxngl4

No-reference bitstream-based impairment detection for high efficiency video coding

Glenn Van Wallendael, Nicolas Staelens, Lucjan Janowski, Jan De Cock, Piet Demeester, Rik Van de Walle
2012 2012 Fourth International Workshop on Quality of Multimedia Experience  
Index Terms-Quality of Experience (QoE), Objective video quality, High Efficiency Video Coding (HEVC)  ...  There is a lot of research invested in H.264/AVC impairment detection models and questions rise if these turn obsolete with a transition to the successor of H.264/AVC, called High Efficiency Video Coding  ...  The research activities described in this paper were funded by Ghent University, the Interdisciplinary Institute for Broadband Technology (IBBT), the Institute for the Promotion of Innovation by Science  ... 
doi:10.1109/qomex.2012.6263845 dblp:conf/qomex/WallendaelSJCDW12 fatcat:jxt4rqp2rbglfpc4ctkuqxaxna

Handcrafted vs Deep Learning Classification for Scalable Video QoE Modeling [article]

Dasari Mallesham, Christina Vlachou, Shruti Sanadhya, Pranjal Sahu, Yang Qiu, Kyu-Han Kim, Samir R. Das
2019 arXiv   pre-print
We achieve a median accuracy of 95% by combining our QoE metrics with the deep learning model, which is a 38% improvement over the state-of-the-art well known techniques.  ...  We show that our metrics achieve a median 90% accuracy by comparing with mean-opinion-score from more than 200 users and 800 video samples over three popular video telephony applications -- Skype, FaceTime  ...  Third, to improve the accuracy, we seek recent success of deep learning solutions [10] [11] [12] by formulating the video quality assessment as a classification problem.  ... 
arXiv:1901.03404v1 fatcat:42btigmtcfdnnn62khuiack53i

Encoder-Decoder Based LSTM Model to Advance User QoE in 360-Degree Video

Muhammad Usman Younus, Rabia Shafi, Ammar Rafiq, Muhammad Rizwan Anjum, Sharjeel Afridi, Abdul Aleem Jamali, Zulfiqar Ali Arain
2022 Computers Materials & Continua  
It demands such types of solutions that can be addressed to obtain the user's Quality-of-Experience (QoE). 360-degree videos have already taken up the user's behavior by storm.  ...  This model takes the transforming data instead of taking the direct input to predict the future user movement.  ...  Acknowledgement: We would like to thank all reviewers for reviewing and giving valuable comments to improve the manuscript's quality.  ... 
doi:10.32604/cmc.2022.022236 fatcat:4vczirpgn5dl5dqwnwtcl736mi

A Regression Method for real-time video quality evaluation

Maria Torres Vega, Decebal Constantin Mocanu, Antonio Liotta
2016 Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media - MoMM '16  
We benchmark our metric against the FR metric VQM (Video Quality Metric), finding a very strong correlation factor.  ...  In this work, we introduce a regression-based video quality metric that is simple enough for real-time computation on thin clients, and comparably as accurate as state-of-the-art Full-Reference (FR) metrics  ...  The method used is bound to have a sensitive effect on the performance of the prediction models and, ultimately, on the accuracy of the NR metric.  ... 
doi:10.1145/3007120.3007125 fatcat:xe4mebnkwjaa5oqap4iuz6hbki

A Survey of Machine Learning Techniques for Video Quality Prediction from Quality of Delivery Metrics

Obinna Izima, Ruairí Fréin, Ali Malik
2021 Electronics  
ML has been applied to predict the quality of video streams.  ...  In response, numerous solutions have been proposed to tackle the challenge of video quality prediction from QoD-derived metrics.  ...  • A review of the applications of ML techniques for predicting QoD metrics with the aim of improving video quality.  ... 
doi:10.3390/electronics10222851 fatcat:qinumw4b2rhvpmx4m7r62vk7ze

No-reference Video Quality Estimation Based on Machine Learning for Passive Gaming Video Streaming Applications

Nabajeet Barman, Emmanuel Jammeh, Seyed Ali Ghorashi, Maria G. Martini
2019 IEEE Access  
We evaluate their performance on different gaming video datasets and show that the proposed models outperform the current state-of-the-art no-reference metrics, while also reaching a prediction accuracy  ...  INDEX TERMS Quality assessment, no reference, gaming video streaming, machine learning, regression, quality of experience, video quality metrics.  ...  In [23] , the authors used SVR for quality prediction, compared the performance with different visual quality predictors and reported improvement in prediction accuracy.  ... 
doi:10.1109/access.2019.2920477 fatcat:4fhcaprqerc4npacqzxfqfpr7m

Improving the verification process of video quality metrics

Christian Keimel, Tobias Oelbaum, Klaus Diepold
2009 2009 International Workshop on Quality of Multimedia Experience  
We will highlight in detail five steps that should be followed in order to improve the overall quality of the verification process of video quality metrics: using a large and diverse data base, planing  ...  The most important step in the development process of a video quality metric is its verification with regards to the subjective quality experience.  ...  Therefore we propose that the following five steps should be considered in order to improve the overall quality of the verification process in the research on video quality metrics: Table 1 : 1 Pearson  ... 
doi:10.1109/qomex.2009.5246966 fatcat:4mkwejkc7vd23kjg4fdbapx3py

Predictive No-Reference Assessment of Video Quality [article]

Maria Torres Vega, Decebal Constantin Mocanu, Antonio Liotta
2016 arXiv   pre-print
Among the various means to evaluate the quality of video streams, No-Reference (NR) methods have low computation and may be executed on thin clients.  ...  In this work, we present an NR method that combines machine learning with simple NR metrics to achieve a quality index comparably as accurate as the Video Quality Metric (VQM) Full-Reference algorithm.  ...  ACKNOWLEDGMENT This work has been carried out in the context of the European Research Council project BROWSE (Beam-steered Reconfigurable Optical-Wireless System for Energy-efficient communication -Grant  ... 
arXiv:1604.07322v2 fatcat:2wc4zmomf5h3fapcjud2vmumse
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