The assessment of perceived quality based on psychophysiological methods recently gained attraction as it potentially overcomes certain flaws of psychophysical approaches. Although studies report promising results, it is not possible to arrive at decisive and comparable conclusions that recommend the use of one or another method for a specific application or research question. The video quality expert group started a project on psychophysiological quality assessment to study these novel approaches and to develop a test plan that enables more systematic research. This test plan comprises of a specifically designed set of quality annotated video sequences, suggestions for psychophysiological methods to be studied in quality assessment, and recommendations for the documentation and publications of test results. The test plan is presented in this article.

In this study, we investigate a VR simulator of a forestry crane used for loading logs onto a truck, mainly looking at Quality of Experience (QoE) aspects that may be relevant for task completion, but also whether there are any discomfort related symptoms experienced during task execution. A QoE test has been designed to capture both the general subjective experience of using the simulator and to study task performance. Moreover, a specific focus has been to study the effects of latency on the subjective experience, with regards to delays in the crane control interface. A formal subjective study has been performed where we have added controlled delays to the hand controller (joystick) signals. The added delays ranged from 0 ms to 800 ms. We found no significant effects of delays on the task performance on any scales up to 200 ms. A significant negative effect was found for 800 ms added delay. The Symptoms reported in the Simulator Sickness Questionnaire (SSQ) was significantly higher for all the symptom groups, but a majority of the participants reported only slight symptoms. Two out of thirty test persons stopped the test before finishing due to their symptoms.

In this paper, we investigate how different viewing positions affect a user's Quality of Experience (QoE) and performance in an immersive telepresence system. A QoE experiment has been conducted with 27 participants to assess the general subjective experience and the performance of remotely operating a toy excavator. Two view positions have been tested, an overhead and a ground-level view, respectively, which encourage reliance on stereoscopic depth cues to different extents for accurate operation. Results demonstrate a significant difference between ground and overhead views: the ground view increased the perceived difficulty of the task, whereas the overhead view increased the perceived accomplishment as well as the objective performance of the task. The perceived helpfulness of the overhead view was also significant according to the participants.

Advances in imaging and display engineering have given rise to new and improved image and videoapplications that aim to maximize visual quality under given resource constraints (e.g., power, bandwidth).Because the human visual system is an imperfect sensor, the images/videos can be represented in a mathematicallylossy fashion but with enough fidelity that the losses are visually imperceptible—commonly termed“visually lossless.” Although a great deal of research has focused on gaining a better understanding ofthe limits of human vision when viewing natural images/video, a universally or even largely accepted definitionof visually lossless remains elusive. Differences in testing methodologies, research objectives, and targetapplications have led to multiple ad-hoc definitions that are often difficult to compare to or otherwise employ inother settings. We present a compendium of technical experiments relating to both vision science and visualquality testing that together explore the research and business perspectives of visually lossless image quality,as well as review recent scientific advances. Together, the studies presented in this paper suggest that a singledefinition of visually lossless quality might not be appropriate; rather, a better goal would be to establish varyinglevels of visually lossless quality that can be quantified in terms of the testing paradigm.

In this study, we investigate a VR simulator of a forestrycrane used for loading logs onto a truck, mainly looking at Qualityof Experience (QoE) aspects that may be relevant for taskcompletion, but also whether there are any discomfort relatedsymptoms experienced during task execution. The QoE test hasbeen designed to capture both the general subjective experience ofusing the simulator and to study task completion rate. Moreover, aspecific focus has been to study the effects of latency on thesubjective experience, with regards both to delays in the cranecontrol interface as well as lag in the visual scene rendering in thehead mounted display (HMD). Two larger formal subjectivestudies have been performed: one with the VR-system as it is andone where we have added controlled delay to the display updateand to the joystick signals. The baseline study shows that mostpeople are more or less happy with the VR-system and that it doesnot have strong effects on any symptoms as listed in the SSQ. In thedelay study we found significant effects on Comfort Quality andImmersion Quality for higher Display delay (30 ms), but verysmall impact of joystick delay. Furthermore, the Display delay hadstrong influence on the symptoms in the SSQ, as well as causingtest subjects to decide not to continue with the completeexperiments, and this was also found to be connected to the longerDisplay delays (≥ 20 ms).

This paper analyzes how an experimenter can balance errors in subjective video quality tests betweenthe statistical power of finding an effect if it is there and not claiming that an effect is there if the effect is not there,i.e., balancing Type I and Type II errors. The risk of committing Type I errors increases with the number ofcomparisons that are performed in statistical tests. We will show that when controlling for this and at thesame time keeping the power of the experiment at a reasonably high level, it is unlikely that the number oftest subjects that are normally used and recommended by the International Telecommunication Union (ITU),i.e., 15 is sufficient but the number used by the Video Quality Experts Group (VQEG), i.e., 24 is more likelyto be sufficient. Examples will also be given for the influence of Type I error on the statistical significance ofcomparing objective metrics by correlation. We also present a comparison between parametric and nonparametricstatistics. The comparison targets the question whether we would reach different conclusions on the statisticaldifference between the video quality ratings of different video clips in a subjective test, based on thecomparison between the student T-test and the Mann–Whitney U-test. We found that there was hardly a differencewhen few comparisons are compensated for, i.e., then almost the same conclusions are reached. Whenthe number of comparisons is increased, then larger and larger differences between the two methods arerevealed. In these cases, the parametric T-test gives clearly more significant cases, than the nonparametrictest, which makes it more important to investigate whether the assumptions are met for performing a certaintest.

Executing an accurate full-reference metric such as VQM can take minutes in an average computer for just one user. Therefore, it can be unfeasible to analyze all the videos received by users in an IPTV network for example consisting of 10.000 users using a single computer running the VQM metric. One solution can be to use a lightweight no-reference metrics in addition to the full-reference metric mentioned. Lightweight no-reference metrics can be used for discarding potential situations to evaluate because they are accurate enough for that task, and then the full-reference metric VQM can be used when more accuracy is needed. The work in this paper is focused on determining the maximum number of situations/users that can be analyzed simultaneously using the VQM metric in a computer with good performance. The full-reference metric is applied on the transmitter using a method specified in the recommendation ITU BT.1789. The best performance achieved was 112.8 seconds per process. 

This paper analyzes how an experimenter can balance errors in subjective video quality tests between the statistical power of finding an effect if it is there and not claiming that an effect is there if the effect it is not there i.e. balancing Type I and Type II errors. The risk of committing Type I errors increases with the number of comparisons that are performed in statistical tests. We will show that when controlling for this and at the same time keeping the power of the experiment at a reasonably high level, it will require more test subjects than are normally used and recommended by international standardization bodies like the ITU. Examples will also be given for the influence of Type I error on the statistical significance of comparing objective metrics by correlation.

The ever-increasing need for displaying in-vehicle visual information in a non-distracting way requires a high visual performance of automotive displays. For their procurement, deep technical and supply-chain knowledge is required. Therefore, based on our comparisons of in-vehicle and laboratory visual-performance measurements, we propose a certification system for automotive display panels. 

This paper will explore the mobile and business perspectives of visually lossless image quality, as well as review recent scientific advances. It is the outcome from the Special Session on Visually Lossless Video Quality for Modern Devices: Research and Industry Perspectives organized at the Human Vision and Electronic Imaging 2017 by IS&T at San Francisco Airport, Burlingame, California, USA, Jan 29 - Feb 2, 2017. It summarizes four presentations and a panel discussion.