Subjective assessment of H.264/AVC video sequences transmitted over a noisy channel

Simone, F.; Naccari, Matteo; Tagliasacchi, Marco; Dufaux, Frédéric; Tubaro, Stefano; Ebrahimi, Touradj

doi:10.1109/qomex.2009.5246952

Cited by 119 publications

(76 citation statements)

References 6 publications

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“…Several researchers have conducted subjective video quality studies with various aims [5]- [10]. Significant effort has also been applied to designing objective algorithms that are capable of predicting visual quality with high correlation against subjective perception [11]- [14].…”

Section: Introductionmentioning

confidence: 99%

Video Quality Assessment on Mobile Devices: Subjective, Behavioral and Objective Studies

Moorthy

Choi

Bovik

et al. 2012

IEEE J. Sel. Top. Signal Process.

268

168

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Abstract-We introduce a new video quality database that models video distortions in heavily-trafficked wireless networks and that contains measurements of human subjective impressions of the quality of videos. The new LIVE Mobile Video Quality Assessment (VQA) database consists of 200 distorted videos created from 10 RAW HD reference videos, obtained using a RED ONE digital cinematographic camera. While the LIVE Mobile VQA database includes distortions that have been previously studied such as compression and wireless packet-loss, it also incorporates dynamically varying distortions that change as a function of time, such as frame-freezes and temporally varying compression rates. In this article, we describe the construction of the database and detail the human study that was performed on mobile phones and tablets in order to gauge the human perception of quality on mobile devices. The subjective study portion of the database includes both the differential mean opinion scores (DMOS) computed from the ratings that the subjects provided at the end of each video clip, as well as the continuous temporal scores that the subjects recorded as they viewed the video. The study involved over 50 subjects and resulted in 5,300 summary subjective scores and time-sampled subjective traces of quality. In the behavioral portion of the article we analyze human opinion using statistical techniques, and also study a variety of models of temporal pooling that may reflect strategies that the subjects used to make the final decision on video quality. Further, we compare the quality ratings obtained from the tablet and the mobile phone studies in order to study the impact of these different display modes on quality. We also evaluate several objective image and video quality assessment (IQA/VQA) algorithms with regards to their efficacy in predicting visual quality. A detailed correlation analysis and statistical hypothesis testing is carried out. Our general conclusion is that existing VQA algorithms are not well-equipped to handle distortions that vary over time. The LIVE Mobile VQA database, along with the subject DMOS and the continuous temporal scores is being made available to researchers in the field of VQA at no cost in order to further research in the area of video quality assessment. Index Terms-Mobile video quality, objective algorithm evaluations, subjective quality, video quality assessment, video quality database.

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Section: Introductionmentioning

confidence: 99%

Video Quality Assessment on Mobile Devices: Subjective, Behavioral and Objective Studies

Moorthy

Choi

Bovik

et al. 2012

IEEE J. Sel. Top. Signal Process.

268

168

View full text Add to dashboard Cite

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“…From the dataset, we took six video sequences which were also used in subjective evaluations in. 21 The six sequences are all in I420 raw progressive format, with 10 seconds long at 4CIF spatial resolution (704×576 pixels). They are referred to as Crowdrun, Duckstakeoff, Harbour, Ice, Parkjoy and Soccer respectively.…”

Section: Epfl-polimi Video Quality Assessment Databasementioning

confidence: 99%

Towards an animated JPEG

Theytaz

Lin

McNally

et al. 2016

Applications of Digital Image Processing XXXIX

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Recently, short animated image sequences have become very popular in social networks. Most animated images are represented in GIF format. In this paper we propose an animated JPEG format, called aJPEG, which allows the standard JPEG format to be extended in a backward compatible way in order to cope with animated images. After presenting the proposed format, we illustrate it using two prototype applications: the first in form of a GIF-to-aJPEG converter on a personal computer and the second in form of an aJPEG viewer on a smart phone. The paper also reports the performance evaluation of aJPEG when compared to GIF. Experimental results show that aJPEG outperforms animated GIF in both file size overhead and image quality.

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“…Similarly for impairments: 'Very annoying', 'Annoying', 'Slightly annoying', 'Perceptible' and 'Imperceptible'. There is also a comparisons scale for Differential MOS (DMOS) going from 'Much worse' to 'Much better' with an additional value in the middle 'The same '. A typical example of a subjective assessment using ACR has been executed in [77]. The assessment is on quality degradation of error-prone network transmission.…”

Section: Rating the Qualitymentioning

confidence: 99%

Computational Inference and Control of Quality in Multimedia Services

Menkovski

2015

Springer Theses

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Please check the document version of this publication:• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement:www.tue.nl/taverne Take down policyIf you believe that this document breaches copyright please contact us at:openaccess@tue.nl providing details and we will investigate your claim. Copyright c 2013 by Vlado Menkovski All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means without the prior written consent of the author. Typeset using L A T E X, printed in The NetherlandsTo my parents, Angel who dedicated his life to his sons and Snežana whose strength inspires me deeply. SummaryQuality is the degree of excellence we expect of a service or a product. It is also one of the key factors that determine its value. For multimedia services, understanding the experienced quality means understanding how the delivered fidelity, precision and reliability correspond to the users' expectations. Yet the quality of multimedia services is inextricably linked to the underlying technology. It is developments in video recording, compression and transport as well as display technologies that enables high quality multimedia services to become ubiquitous. The constant evolution of these technologies delivers a steady increase in performance, but also a growing level of complexity. As new technologies stack on top of each other the interactions between them and their components become more intricate and obscure. In this environment optimizing the delivered quality of multimedia services becomes increasingly challenging. The factors that affect the experienced quality, or Quality of Experience (QoE), tend to have complex non-linear relat...

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Subjective assessment of H.264/AVC video sequences transmitted over a noisy channel

Cited by 119 publications

References 6 publications

Video Quality Assessment on Mobile Devices: Subjective, Behavioral and Objective Studies

Video Quality Assessment on Mobile Devices: Subjective, Behavioral and Objective Studies

Towards an animated JPEG

Computational Inference and Control of Quality in Multimedia Services

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