Modelling of spatio–temporal interaction for video quality assessment

Huynh-Thu, Quan; Ghanbari, M.

doi:10.1016/j.image.2010.03.006

Cited by 18 publications

(5 citation statements)

References 23 publications

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“…The effect of interactions between bit-rate levels and temporal freezes in video playback on the quality have been evaluated in [78] also by means of an ACR subjective study. They concluded that the video quality is affected by both types of impairments, however the temporal impairment have a more intensive effect.…”

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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Section: Rating the Qualitymentioning

confidence: 99%

Computational Inference and Control of Quality in Multimedia Services

Menkovski

2015

Springer Theses

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“…The authors of (Tran & Mellouk, 2010) implement a QoE model for network services by defining key performance indicators of service availability, accessibility, continuality, responsiveness, and delay. Other efforts focus on freezes in the playback (Huynh-Thu & Ghanbari, 2010) and their relationship with the spatial quality.…”

Section: Factors That Affect Qoe In Multimedia Streamingmentioning

confidence: 99%

QoE for Mobile Streaming

Menkovski¹,

Liotta²

2012

Mobile Multimedia - User and Technology Perspectives

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“…A nonlinear model was proposed to integrate the contributions of a spatial quality and a temporal quality. 18 However, the combination performed at the video level is not efficient since the temporal quality of the video is closely tied to the spatial distortion of individual frames.…”

Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Video Quality Assessment Based on Two-Level Temporal Pooling

Yang

Wan

2011

Int. J. Image Grap.

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In this paper, a video quality assessment method based on two-level temporal pooling is proposed. By dividing a video sequence into groups of frames (GOFs) with variable lengths, a short-term temporal pooling is performed first at the eye fixation level to obtain the GOF quality. The determination of the GOF size is based on empirical observations from subjective tests that evaluate the duration of successive frames based on which steady quality judgment can be made by the human visual system. The video quality is further obtained by a second level of long-term temporal pooling using the GOF quality. The impact of strong impairment in part of the video on the cognitive system is incorporated in the proposed method for video quality assessment. Extensive experimental results have demonstrated the effectiveness of the proposed method for spatial-temporal distortion evaluation considering both regular and irregular frame loss.Keywords: Group of frame; two-level temporal pooling; video quality assessment; frame loss. Int. J. Image Grap. 2011.11:235-249. Downloaded from www.worldscientific.com by SIMON FRASER UNIVERSITY on 03/15/15. For personal use only.

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Modelling of spatio–temporal interaction for video quality assessment

Cited by 18 publications

References 23 publications

Computational Inference and Control of Quality in Multimedia Services

Computational Inference and Control of Quality in Multimedia Services

QoE for Mobile Streaming

Spatial-Temporal Video Quality Assessment Based on Two-Level Temporal Pooling

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