Perceptual-based quality assessment for audio–visual services: A survey

You, Junyong; Reiter, Ulrich; Hannuksela, Miska M.; Gabbouj, Moncef; Perkis, Andrew

doi:10.1016/j.image.2010.02.002

Cited by 118 publications

(78 citation statements)

References 55 publications

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“…Following the recommendation [13], a non-symmetrical logistic function is used. Its mathematical expression is given by (1), where a and b are the parameters of the function, D is the distortion output of the QuID, and u min and u max are the minimum and maximum subjective scores for the analyzed event.…”

Section: Resultsmentioning

confidence: 99%

“…Using the mapping described by (1), with D equals to the duration of the impairment (t), the RMSE was 0.133 considering all the events of audio distortions.…”

Section: ) Audio Distortionsmentioning

confidence: 99%

“…to analyze the quality provided by a video coding algorithm. Therefore, MOS-based metrics have been mainly targeted to design and evaluate media encoders, as they are more accurate than simple Peak Signal to Noise Ratio (PSNR) analyses, and much more practical than subjective quality assessment sessions [1].…”

Section: Introductionmentioning

confidence: 99%

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Qualitative Monitoring of Video Quality of Experience

Pérez¹,

Gutiérrez

Ruiz³

et al. 2011

2011 IEEE International Symposium on Multimedia

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Abstract-Real-time monitoring of multimedia Quality of Experience is a critical task for the providers of multimedia delivery services: from television broadcasters to IP content delivery networks or IPTV. For such scenarios, meaningful metrics are required which can generate useful information to the service providers that overcome the limitations of pure Quality of Service monitoring probes. However, most of objective multimedia quality estimators, aimed at modeling the Mean Opinion Score, are difficult to apply to massive quality monitoring. Thus we propose a lightweight and scalable monitoring architecture called Qualitative Experience Monitoring (QuEM), based on detecting identifiable impairment events such as the ones reported by the customers of those services. We also carried out a subjective assessment test to validate the approach and calibrate the metrics. Preliminary results of this test set support our approach.

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Section: Resultsmentioning

confidence: 99%

“…Using the mapping described by (1), with D equals to the duration of the impairment (t), the RMSE was 0.133 considering all the events of audio distortions.…”

Section: ) Audio Distortionsmentioning

confidence: 99%

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Qualitative Monitoring of Video Quality of Experience

Pérez¹,

Gutiérrez

Ruiz³

et al. 2011

2011 IEEE International Symposium on Multimedia

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“…Perceptual assessment for Quality of Experience (QoE) is becoming a critical issue in multimedia services [1]. Even though subjective quality assessment is the most reliable way to evaluate the perceived video quality, it is always expensive in the manpower and time costs.…”

Section: Introductionmentioning

confidence: 99%

Visual attention tuned spatio-velocity contrast sensitivity for video quality assessment

You

Ebrahimi

Perkis

2011

2011 IEEE International Conference on Multimedia and Expo

Self Cite

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Contrast sensitivity is an important characteristic of the human visual system (HVS), which is widely used in image and video signal processing. For visual quality assessment, static spatio-temporal frequency based contrast sensitivity function (CSF) is often used, while the contrast sensitivity can also be affected by smooth pursuit of eyes when tracking attentive regions in the field of view. This paper proposes to tune CSF based on an attention map derived from a visual attention model. The tuned CSF formulated by spatial frequency, temporal velocity, and visual attention map is used to filter video signals in order to construct a quality metric according to the difference of the filtered signals between a reference video and its distorted version. Experimental results demonstrate that the proposed attention tuned spatio-velocity CSF outperforms the traditional spatio-temporal CSF in evaluating the perceived video quality.

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“…This is of high importance when it comes to streaming services as well as real time applications for one-way or two-way communication of audio and video. Several studies have been published focused on both the effects of audio and video skewness and on reference models to handle synchronization in different ways, at IP level as well as application level [1,7,23,25]. It is shown that viewers perceive audio and video to be synchronized with an audio-to-video skew up to about 80 ms but also that there is a higher tolerance for video ahead of audio than vice versa.…”

mentioning

confidence: 99%

A robust method for estimating synchronization and delay of audio and video for communication services

Rossholm

Lövström

2014

Multimed Tools Appl

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PostprintThis is the accepted version of a paper published in Multimedia tools and applications. This paper has been peer-reviewed but does not include the final publisher proof-corrections or journal pagination. Abstract One of the main contributions to the quality of experience in streaming services or in two-way communication of audio and video applications is synchronization. This has been shown in several studies and experiments but methods to measure synchronization are less frequent, especially for situations without internal access to the application and independent of platform and device. In this paper we present a method for measuring synchronization skewness as well as delay for audio and video. The solution incorporates audio and video reference streams, where audio and video frames are marked with frame numbers which are decoded on the receiver side to enable calculation of synchronization and delay. The method has been verified in a two-way communication application in a transparent network with and without inserting known delays, as well as in a network with 5 and 10 % packet loss levels. The method can be used for both streaming and two-way communication services, both with and without access to the internal structures, and enables measurements of applications running on e.g. smartphones, tablets, and laptops under various conditions.

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Perceptual-based quality assessment for audio–visual services: A survey

Cited by 118 publications

References 55 publications

Qualitative Monitoring of Video Quality of Experience

Qualitative Monitoring of Video Quality of Experience

Visual attention tuned spatio-velocity contrast sensitivity for video quality assessment

A robust method for estimating synchronization and delay of audio and video for communication services

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