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54
Video Quality Measurement Standards – Current Status and Trends
"... Abstract—With the wide-spread use of digital video, quality considerations have become essential, and industry demand for video quality measurement standards is rising. Various organizations are working on such standards. This paper reviews some of the existing standards documents, on-going work and ..."
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Abstract—With the wide-spread use of digital video, quality considerations have become essential, and industry demand for video quality measurement standards is rising. Various organizations are working on such standards. This paper reviews some of the existing standards documents, on-going work and future trends in this space. Index Terms—Video quality measurement, subjective experiments, objective quality metrics, Mean Opinion Score (MOS), standardization I.
Pick your Layers wisely- A Quality Assessment of H.264 Scalable Video Coding for Mobile Devices
"... Abstract—Multi-dimensional video scalability as defined in H.264/SVC is a promising concept to efficiently adapt encoded streams to individual device capabilities and network conditions. However, we still lack a thorough understanding of how to automate scaling procedure in order to achieve an optim ..."
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Abstract—Multi-dimensional video scalability as defined in H.264/SVC is a promising concept to efficiently adapt encoded streams to individual device capabilities and network conditions. However, we still lack a thorough understanding of how to automate scaling procedure in order to achieve an optimal quality of experience (QoE) for end uses. In this paper we present and discuss the results of a subjective quality assessment we performed on mobile devices to investigate the effects of multi-dimensional scalability on human quality perception. Our study reveals that QoE degrades nonmonotonically with bitrate and that scaling order preferences are content-dependent. We confirm previous studies which found common objective metrics to fail for scalable content, but we also show that even scalability-aware models perform poor. Our results are supposed to help improving the design of quality metrics and adaptive network services for scalable streaming applications. I.
Subjective Quality Evaluation of Foveated Video Coding Using Audio-Visual Focus of Attention
"... Abstract—This paper presents a foveated coding method using audio-visual focus of attention and its evaluation through extensive subjective experiments on both standard-definition and high-definition sequences. Regarding a sound-emitting region as the location drawing the human attention, the method ..."
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Abstract—This paper presents a foveated coding method using audio-visual focus of attention and its evaluation through extensive subjective experiments on both standard-definition and high-definition sequences. Regarding a sound-emitting region as the location drawing the human attention, the method applies varying quality levels in an image frame according to the distance of a pixel to the identified sound source. Two experiments are presented to prove the efficiency of the method. Experiment 1 examines the validity and effectiveness of the method in comparison to the constant quality coding for high-quality conditions. In Experiment 2, the method is compared to the fixed bit rate coding for low quality conditions where coding artifacts are noticeable. The results demonstrate that the foveated coding method provides considerable coding gain without significant quality degradation, but uneven distributions of the coding artifacts (blockiness) by the method are often less preferred than the uniform distribution of the artifacts. Additional interesting findings are also discussed, such as content dependence of the performance of the method, the memory effect in multiple viewings, and the difference in the quality perception for frame size variations. Index Terms—Audio-visual focus of attention, content dependence, foveated coding, H.264/AVC, memory effect, quality of experience, subjective quality assessment. I.
An Adaptive Video Streaming Control System: Modelling, Validation, and Performance Evaluation
"... Abstract—Adaptive video streaming is a relevant advancement with respect to classic progressive download streaming a-la YouTube. Among the different approaches, the video stream-switching technique is getting wide acceptance, being adopted by Microsoft, Apple and by popular video streaming services ..."
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Abstract—Adaptive video streaming is a relevant advancement with respect to classic progressive download streaming a-la YouTube. Among the different approaches, the video stream-switching technique is getting wide acceptance, being adopted by Microsoft, Apple and by popular video streaming services such as Akamai, Netflix, Hulu, Vudu, and Livestream. In this paper, we present a model of the automatic video stream-switching employed by one of these leading video streaming services along with a description of the client-side communication and control protocol. From the control architecture point of view, the automatic adaptation is achieved by means of two interacting control loops having the controllers at the client and the actuators at the server: one loop is the buffer controller, which aims at steering the client playout buffer to a target length by regulating the server sending rate; the other one implements the stream-switching controller and aims at selecting the video level. A detailed validation of the proposed model has been carried out through experimental measurements in an emulated scenario. Index Terms—Adaptive video streaming, stream-switching, modelling, performance evaluation I.
Deep Machine Learning with Spatio-Temporal Inference
, 2012
"... This Dissertation is brought to you for free and open access by the Graduate School at Trace: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of Trace: Tennessee Research and Creative Exchange. For more ..."
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This Dissertation is brought to you for free and open access by the Graduate School at Trace: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of Trace: Tennessee Research and Creative Exchange. For more
A methodology for assessing video transmission energy consumption and quality
- in: Communications (ICC), 2012 IEEE International Conference on, 2012
"... Abstract—Video traffic has been growing significantly and it is expected to be a large share of the future Internet traffic, within an increasingly mobile environment with scarce resources. In this context, new challenges arise, and energy-efficiency is becoming a key factor for the successful deplo ..."
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Abstract—Video traffic has been growing significantly and it is expected to be a large share of the future Internet traffic, within an increasingly mobile environment with scarce resources. In this context, new challenges arise, and energy-efficiency is becoming a key factor for the successful deployment of mobile networks. The development and validation of mechanisms for energy-efficient video transmission require the measurement of the energy consumption needed for video transmission, considering also the end-user Quality of Experience. This issue is of utmost importance, as users will tailor their application and network usage behaviors based on the perceived quality of the services and on the capabilities of their devices. In this work, an integrated empirical methodology to assess the video transmission energy consumption and quality is proposed. The developed methodology was validated on two distinct testbeds, one with IEEE 802.11 and the other with IEEE 802.16e. Results showed that the proposed methodology enables an accurate assessment of energy consumption with different technologies, while measuring the end-user Quality of Experience. Another contribution of the proposed methodology is the capability to gather data to support the creation and validation of realistic simulation models.
SUBJECTIVE EVALUATION OF A NO-REFERENCE VIDEO QUALITY MONITORING ALGORITHM FOR H.264/AVC VIDEO OVER A NOISY CHANNEL
"... In this paper we evaluate NORM, a NO-Reference video quality Monitoring algorithm we proposed in a previous work, for the pre-diction of the subjective quality of H.264/AVC video transmitted over a noisy packet-switched network. NORM produces an esti-mate of the mean square error distortion at the m ..."
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In this paper we evaluate NORM, a NO-Reference video quality Monitoring algorithm we proposed in a previous work, for the pre-diction of the subjective quality of H.264/AVC video transmitted over a noisy packet-switched network. NORM produces an esti-mate of the mean square error distortion at the macroblock level be-tween the noiseless and noisy sequence, without having access to the former. The output of NORM can be readily converted into a no-reference estimate of the PSNR at the sequence level. We car-ried out an extensive subjective evaluation campaign on CIF and 4CIF resolution sequences encoded with H.264/AVC and transmit-ted over a channel that drops packets at different packet loss rates, to obtain the differential mean opinion scores. Our results show that the estimated PSNR achieves good correlation with the subjective scores, very close to the ones achieved by the PSNR computed in full-reference mode, i.e. as if the noiseless sequence would be avail-able at the decoder. Index Terms — Objective and Subjective video quality assess-ment, no-reference quality assessment. 1.
Preliminary Findings on Image Preference Characterization based on Neurophysiological Signal Analysis
- Towards Objective QoE Modelling”, Fourth International Workshop on Quality of Multimedia Experience (QoMEX), AUS-Yarra Valley
, 2012
"... Image preference is a subjective factor which plays an impor-tant role in Quality-of-Experience (QoE) modelling. Tradi-tionally, preference characterization has been quantified via questionnaires or subjective evaluations. Current advances in neurophysiological signal acquisition, however, have allo ..."
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Image preference is a subjective factor which plays an impor-tant role in Quality-of-Experience (QoE) modelling. Tradi-tionally, preference characterization has been quantified via questionnaires or subjective evaluations. Current advances in neurophysiological signal acquisition, however, have allowed for such “non-measurable ” subjective parameters to be quan-tified objectively. In this pilot study, we explore the use of neurophysiological signals as correlates of image preference characterization. Experiments with seven participants have shown promising results and mental states associated with preferred and non-preferred images, as well as baseline neu-tral state could be classified with above-chance levels. Index Terms — QoE, NIRS, PANS, image preference. 1.
A.: Machine Learning Approach for Quality of Experience Aware Networks
- In: IEEE INCoS (2010
"... Abstract-Efficient management of multimedia services necessitates the understanding of how the quality of these services is perceived by the users. Estimation of the perceived quality or Quality of Experience (QoE) of the service is a challenging process due to the subjective nature of QoE. This pr ..."
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Abstract-Efficient management of multimedia services necessitates the understanding of how the quality of these services is perceived by the users. Estimation of the perceived quality or Quality of Experience (QoE) of the service is a challenging process due to the subjective nature of QoE. This process usually incorporates complex subjective studies that need to recreate the viewing conditions of the service in a controlled environment. In this paper we present Machine Learning techniques for modeling the dependencies of different network and application layer quality of service parameters to the QoE of network services using subjective quality feedback. These accurate QoE prediction models allow us to further develop a geometrical method for calculating the possible remedies per network stream for reaching the desired level of QoE. Finally we present a set of possible network techniques that can deliver the desired improvement to the multimedia streams.
