7 research outputs found

    Including the Effects of Video Content in the ITU-T G.1070 Video Quality Function

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    In this paper we present an enhancement to the video quality estimation model described in ITU-T Recommendation G.1070 “Opinion model for video-telephony applications”, including the effect of video content in the G.1070 video quality function. This enhancement provides a much better approximation of the model results with respect to the perceptual MOS values. SAD (Sum of Absolute Differences) is used as an estimation of the video spatial-temporal activity. The results are based on more than 1500 processed video clips, coded in MPEG-2 and H.264/AVC, in bit rate ranges from 50 kb/s to 12 Mb/s, in SD, VGA, CIF and QCIF display formats

    G.1070 Model Extension at Full HD Resolution for VP9/HEVC Codec

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    HD video streaming, which is gaining in popularity these days requires a large amount of bandwidth. This has resulted in the emergence of newer codecs like H.265/High Efficiency Video Coding (HEVC) and VP9 from Google. These codecs are supposed to provide an excellent video compression to quality ratio. ITU-T describes a standardised parametric model called the G.1070 Opinion Model, which estimates the Quality of Experience (QoE) of any multimedia content. The model estimates three parameters viz. the speech quality alone (Sq), the video quality alone (Vq) and the overall multimedia quality (M q) of the input video. However, it needs to be trained separately for different codecs, video formats and certain other parameters, which can be obtained by carrying out suitable subjective tests. Our contribution in this paper is threefold. First, we carry out a subjective test according to the Recommendation P.910 to estimate the video quality for VP9 codec. Second, for the first time we use the results obtained from the subjective test to find out a set of coefficients that enables us to extend the G.1070 model for VP9 codec at Full HD resolution. Third, we provide an answer as to which is the better codec from H.265/HEVC and VP9 by evaluating their performance against scores obtained from different standard objective tests like the G.1070 model, Video Quality Metric (VQM) model and the Peak Signal to Noise Ratio (PSNR) model

    Profiling Skype video calls: Rate control and video quality

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    Video telephony has recently gained its momentum and is widely adopted by end-consumers. But there have been very few studies on the network impacts of video calls and the user Quality-of-Experience (QoE) under different network conditions. In this paper, we study the rate control and video quality of Skype video calls. We first measure the behaviors of Skype video calls on a controlled network testbed. By varying packet loss rate, propagation delay and bandwidth, we observe how Skype adjusts its rates, FEC redundancy and video quality. We find that Skype is robust against mild packet losses and propagation delays, and can efficiently utilize the available network bandwidth. We also find that Skype employs an overly aggressive FEC protection strategy. Based on the measurement results, we develop rate control model, FEC model, and video quality model for Skype. Extrapolating from the models, we conduct numerical analysis to study the network impacts of Skype. We demonstrate that user back-offs upon quality degradation serve as an effective user-level rate control scheme. We also show that Skype video calls are indeed TCP-friendly and respond to congestion quickly when the network is overloaded.Engineering, Electrical & ElectronicTelecommunicationsEICPCI-S(ISTP)

    Computer-Assisted Algorithms for Ultrasound Imaging Systems

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    Ultrasound imaging works on the principle of transmitting ultrasound waves into the body and reconstructs the images of internal organs based on the strength of the echoes. Ultrasound imaging is considered to be safer, economical and can image the organs in real-time, which makes it widely used diagnostic imaging modality in health-care. Ultrasound imaging covers the broad spectrum of medical diagnostics; these include diagnosis of kidney, liver, pancreas, fetal monitoring, etc. Currently, the diagnosis through ultrasound scanning is clinic-centered, and the patients who are in need of ultrasound scanning has to visit the hospitals for getting the diagnosis. The services of an ultrasound system are constrained to hospitals and did not translate to its potential in remote health-care and point-of-care diagnostics due to its high form factor, shortage of sonographers, low signal to noise ratio, high diagnostic subjectivity, etc. In this thesis, we address these issues with an objective of making ultrasound imaging more reliable to use in point-of-care and remote health-care applications. To achieve the goal, we propose (i) computer-assisted algorithms to improve diagnostic accuracy and assist semi-skilled persons in scanning, (ii) speckle suppression algorithms to improve the diagnostic quality of ultrasound image, (iii) a reliable telesonography framework to address the shortage of sonographers, and (iv) a programmable portable ultrasound scanner to operate in point-of-care and remote health-care applications

    Modelado de calidad percibida de video en televisión digital abierta

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    In this master’s thesis Video Quality Assessment state of the art is reached. Different full reference (FR), reduced reference (RR) and no reference (NR) objective video quality estimation models, previously proposed by the research group, by the academic community or standardized by international organizations, are evaluated and analyzed. Their performance is compared by contrasting their results with ones obtained through subjective video quality evaluations. The ISDB-Tb standard of free-to-air Digital Television (DTV) is deepened, from the point of view of the correct reception and visualization of the DTV signal. Finally, this work contains specific contributions in the area of objective video quality assessment with application in DTV. In this thesis it is proposed and evaluated a new method that combines FR and NR objective models to perform the perceived video quality prediction in real time for the DTV signal. This new approach is based on modern video quality evaluation techniques under a DTV monitoring system with receiver nodes geographically distributed in the coverage area of a DTV station.Sociedad Argentina de Informática e Investigación Operativa (SADIO

    Video Quality Prediction for Video over Wireless Access Networks (UMTS and WLAN)

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    Transmission of video content over wireless access networks (in particular, Wireless Local Area Networks (WLAN) and Third Generation Universal Mobile Telecommunication System (3G UMTS)) is growing exponentially and gaining popularity, and is predicted to expose new revenue streams for mobile network operators. However, the success of these video applications over wireless access networks very much depend on meeting the user’s Quality of Service (QoS) requirements. Thus, it is highly desirable to be able to predict and, if appropriate, to control video quality to meet user’s QoS requirements. Video quality is affected by distortions caused by the encoder and the wireless access network. The impact of these distortions is content dependent, but this feature has not been widely used in existing video quality prediction models. The main aim of the project is the development of novel and efficient models for video quality prediction in a non-intrusive way for low bitrate and resolution videos and to demonstrate their application in QoS-driven adaptation schemes for mobile video streaming applications. This led to five main contributions of the thesis as follows:(1) A thorough understanding of the relationships between video quality, wireless access network (UMTS and WLAN) parameters (e.g. packet/block loss, mean burst length and link bandwidth), encoder parameters (e.g. sender bitrate, frame rate) and content type is provided. An understanding of the relationships and interactions between them and their impact on video quality is important as it provides a basis for the development of non-intrusive video quality prediction models.(2) A new content classification method was proposed based on statistical tools as content type was found to be the most important parameter. (3) Efficient regression-based and artificial neural network-based learning models were developed for video quality prediction over WLAN and UMTS access networks. The models are light weight (can be implemented in real time monitoring), provide a measure for user perceived quality, without time consuming subjective tests. The models have potential applications in several other areas, including QoS control and optimization in network planning and content provisioning for network/service providers.(4) The applications of the proposed regression-based models were investigated in (i) optimization of content provisioning and network resource utilization and (ii) A new fuzzy sender bitrate adaptation scheme was presented at the sender side over WLAN and UMTS access networks. (5) Finally, Internet-based subjective tests that captured distortions caused by the encoder and the wireless access network for different types of contents were designed. The database of subjective results has been made available to research community as there is a lack of subjective video quality assessment databases.Partially sponsored by EU FP7 ADAMANTIUM Project (EU Contract 214751

    QRP08-1: Opinion Model for Estimating Video Quality of Videophone Services

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