Performance of Video Telephony Services in UMTS using Live Measurements and Network Emulation

Malkowski, M.; Claβen, Daniel

doi:10.1007/s11277-007-9353-5

Cited by 16 publications

(5 citation statements)

References 2 publications

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“…The NTT model is a featurebased system that estimates perceptual quality degradation due to blocking, blurring, and packet losses in network transmission of video [24]. Another model approved for standardization is the Perceptual Evaluation of Video Quality (PEVQ) model from Opticom [25][26][27]. PEVQ is based on an earlier model known as the Perceptual Video Quality Measure (PVQM) developed by Swisscom/KPN Research, Netherlands [28].…”

Section: Feature Based Methodsmentioning

confidence: 99%

Video Quality Assessment

Seshadrinathan

Bovik

2009

The Essential Guide to Video Processing

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Section: Feature Based Methodsmentioning

confidence: 99%

Video Quality Assessment

Seshadrinathan

Bovik

2009

The Essential Guide to Video Processing

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“…However, while detection of distortions is important in some applications, VQA deals with supra-threshold perception, where artifacts in the video sequences are visible and algorithms attempt to quantify the annoyance levels of these distortions. Popular VQA algorithms that embody this approach include the Video Quality Metric (VQM) from NTIA [42], the SSIM index for video [4], [5], Perceptual Video Quality Measure (PVQM) [43] and other algorithms from industry [44], [45], [46], [47], [48]. However, these models also predominantly capture spatial distortions in the video sequence and fail to do an adequate job in capturing temporal distortions in video.…”

Section: Introductionmentioning

confidence: 99%

Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos

Seshadrinathan

Bovik

2010

IEEE Trans. on Image Process.

647

402

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Abstract-There has recently been a great deal of interest in the development of algorithms that objectively measure the integrity of video signals. Since video signals are being delivered to human end users in an increasingly wide array of applications and products, it is important that automatic methods of video quality assessment (VQA) be available that can assist in controlling the quality of video being delivered to this critical audience. Naturally, the quality of motion representation in videos plays an important role in the perception of video quality, yet existing VQA algorithms make little direct use of motion information, thus limiting their effectiveness. We seek to ameliorate this by developing a general, spatio-spectrally localized multiscale framework for evaluating dynamic video fidelity that integrates both spatial and temporal (and spatio-temporal) aspects of distortion assessment. Video quality is evaluated not only in space and time, but also in space-time, by evaluating motion quality along computed motion trajectories. Using this framework, we develop a full reference VQA algorithm for which we coin the term the MOtion-based Video Integrity Evaluation index, or MOVIE index. It is found that the MOVIE index delivers VQA scores that correlate quite closely with human subjective judgment, using the Video Quality Expert Group (VQEG) FRTV Phase 1 database as a test bed. Indeed, the MOVIE index is found to be quite competitive with, and even outperform, algorithms developed and submitted to the VQEG FRTV Phase 1 study, as well as more recent VQA algorithms tested on this database.

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“…While performance evaluation is usually performed by statistical methods, it is recommended that knowledge and data mining techniques can be a very good application in the prediction of users' QoE. Many researchers have pointed out the significance of quality measurement in live mobile networks (Malkowski and Claßen, 2008;Nipp et al, 2007). Simple and advanced regression models with characterisation prospective have been presented in recent research works (Reichl et al, 2013;Pitas et al, 2013b).…”

Section: Introductionmentioning

confidence: 99%

Quality of consumer experience data mining for mobile multimedia communication networks: learning from measurements campaign

Pitas

Panagopoulos

Constantinou

2015

IJWMC

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This paper presents an experimental approach of the major data mining algorithms which can be applied to the quality prediction of provided services by contemporary mobile communication networks. Recent developments in performance evaluation of rollout mobile communication networks are based on drive-test measurement campaigns as well as on network monitoring and management systems. In addition, large measurement databases as well as data warehouses are created, updated and used for a drill-down statistics analysis. An empirical comparison of modern data mining methods for quality prediction and estimation of speech and video telephony services is presented. Learning prediction models are constructed from live network measurements which have been previously collected by experimental equipment during measurement campaigns. Practically and summing up, the proposed engineering approach is general and is applicable to various radio access network technologies during planning and optimisation phases.

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Performance of Video Telephony Services in UMTS using Live Measurements and Network Emulation

Cited by 16 publications

References 2 publications

Video Quality Assessment

Video Quality Assessment

Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos

Quality of consumer experience data mining for mobile multimedia communication networks: learning from measurements campaign

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