Teleoperation systems are increasingly used in remote inspection and maintenance, especially in safety-critical settings. This paper presents findings from a lab study examining user interaction with a teleoperation for airport safety inspection. The study investigates five visual interface configurations: First Person View (FPV), Third Person View (TPV), Augmented FPV, FPV+TPV, and Augmented FPV+TPV. Eighteen participants completed inspection tasks under each condition and rated interface helpfulness, workload (NASA-TLX), and simulator sickness. The result was confirmed by bootstrapping with 1000 iterations. Results showed that all view configurations were rated more helpful than TPV alone, with FPV-based combinations improving depth perception and spatial understanding. NASA-TLX revealed cognitive effort, while SSQ scores decreased post-task, particularly in oculomotor symptoms, suggesting adaptation. These findings support continued research into optimising visual interfaces for teleoperation in safety-critical settings.

Remote control technology for machines and robots has experienced significant advancement in many domains where visual information delivery is essential. Safety management at airports is one field that benefits from remote control systems, enabling operators to scan the airstrip for obstacles and debris. Depth perception and proper view position are critical in remote control systems, where operators need to accurately perceive 3D coordinates and maintain an appropriate perspective for performing tasks from a distance. This Demo paper presents a laboratory platform for an experimental study on human interaction with remote control systems using visual interfaces for inspection tasks to enhance airport safety management. The platform can evaluate the user experience of interfaces provided by First Person View, Third Person View, and Augmentation technologies. This platform enables exploration through controlled experiments and by user tests. These provide an avenue for assessing how these interfaces may affect human performance, depth perception, and user experience when conducting inspection tasks remotely. The findings will shed light on the strengths and limitations of each interface type, offering insights into their potential applications in various domains such as industrial inspection, surveillance, and remote exploration.

Abstract The International Football Association Board decided to introduce Video Assistant Referee (VAR) in 2018. This led to the need to develop methods for quality control of the VAR-systems. This article focuses on the important aspect to evaluate the video quality. Video Quality assessment has matured in the sense that there are standardized, commercial products and established open-source solutions to measure it with objective methods. Previous research has primarily focused on the end-user quality assessment. How to assess the video in the contribution phase of the chain is less studied. The novelties of this study are two-fold: 1) The user study is specifically targeting video experts i.e., to assess the perceived quality of video professionals working with video production. 2) Six video quality models have been independently benchmarked against the user data and evaluated to show which of the models could provide the best predictions of perceived quality. The independent evaluation is important to get unbiased results as shown by the Video Quality Experts Group. An experiment was performed involving 25 video experts in which they rated the perceived quality. The video formats tested were High-Definition TV both progressive and interlaced as well as a quarters size format that was scaled down half the size in both width and height. The videos were encoded with both H.264 and Motion JPEG for the full size but only H.264 for the quarter size. Bitrates ranged from 80 Mbit/s down to 10 Mbit/s. We could see that for H.264 that the quality was overall very good but dropped somewhat for 10 Mbit/s. For Motion JPEG the quality dropped over the whole range. For the interlaced format the degradation that was based on a simple deinterlacing method did receive overall low ratings. For the quarter size three different scaling algorithms were evaluated. Lanczos performed the best and Bilinear the worst. The performance of six different video quality models were evaluated for 1080p and 1080i. The Video Quality Metric for Variable Frame Delay had the best performance for both formats, followed by Video Multimethod Assessment Fusion method and the Video Quality Metric General model.

Tele-operated driving enables industrial operators to control heavy machinery remotely. By doing so, they could work in improved and safe workplaces. However, some challenges need to be investigated while presenting visual information from on-site scenes for operators sitting at a distance in a remote site. This paper discusses the impact of video quality (spatial resolution), field of view, and latency on users' depth perception, experience, and performance in a lab-based tele-operated application. We performed user experience evaluation experiments to study these impacts. Overall, the user experience and comfort decrease while the users' performance error increases with an increase in the glass-to-glass latency. The user comfort reduces, and the user performance error increases with reduced video quality (spatial resolution).

Recent advancement in multimedia and communication network technology have made interactive multimedia and tele-operation applications possible. Teledriving, teleoperation, and video-based remote-controlling require real-time live-video streaming and are delay critical in principle. Supporting such applications over wireless networks for mobile users can pose fundamental challenges in maintaining video quality and service latency requirements. This paper investigates the factors affecting the end-to-end delay in a video-based, remotely controlled moving platform application. It involves the real-time acquisition of environmental information (visually) and the delay-sensitive video streaming to remote operators over wireless networks. This paper presents an innovative experimental testbed developed using a remote-controlled toy truck, off-the-shelf cameras, and wireless fidelity (Wi-Fi) network. It achieves ultra-low end-to-end latency and helped us in performing the delay, network, and video quality evaluations. Extending the experimental study, we also propose a real-time live-media streaming control (RTSC) algorithm that maximizes the video quality by selecting the best streaming (network, video, and camera) configuration while meeting the delay and network availability constraints. RTSC improves the live-streaming video quality by about 33% while meeting the ultra-low latency (< 200 milliseconds) requirement under constrained network availability conditions.

Abstract The research domain on the Quality of Experience (QoE) of 2D video streaming has been well established. However, a new video format is emerging and gaining popularity and availability: VR 360-degree video. The processing and transmission of 360-degree videos brings along new challenges such as large bandwidth requirements and the occurrence of different distortions. The viewing experience is also substantially different from 2D video, it offers more interactive freedom on the viewing angle but can also be more demanding and cause cybersickness. The first goal of this article is to complement earlier research by Tran, et al. (2017) [39] testing the effects of quality degradation, freezing, and content on the QoE of 360-videos. The second goal is to test the contribution of visual attention as an influence factor in the QoE assessment. Data was gathered through subjective tests where participants watched degraded versions of 360-videos through a Head-Mounted Display with integrated eye-tracking sensors. After each video they answered questions regarding their quality perception, experience, perceptual load, and cybersickness. Our results showed that the participants rated the overall QoE rather low, and the ratings decreased with added degradations and freezing events. Cyber sickness was found not to be an issue. The effects of the manipulations on visual attention were minimal. Attention was mainly directed by content, but also by surprising elements. The addition of eye-tracking metrics did not further explain individual differences in subjective ratings. Nevertheless, it was found that looking at moving objects increased the negative effect of freezing events and made participants less sensitive to quality distortions. More research is needed to conclude whether visual attention is an influence factor on the QoE in 360-video.

Recently an impressive development in immersive technologies, such as Augmented Reality (AR), Virtual Reality (VR) and 360${^\circ }$video, has been witnessed. However, methods for quality assessment have not been keeping up. This paper studies quality assessment of 360${^\circ }$video from the cross-lab tests (involving ten laboratories and more than 300 participants) carried out by the Immersive Media Group (IMG) of the Video Quality Experts Group (VQEG). These tests were addressed to assess and validate subjective evaluation methodologies for 360${^\circ }$video. Audiovisual quality, simulator sickness symptoms, and exploration behavior were evaluated with short (from 10 seconds to 30 seconds) 360${^\circ }$sequences. The following factors’ influences were also analyzed: assessment methodology, sequence duration, Head-Mounted Display (HMD) device, uniform and non-uniform coding degradations, and simulator sickness assessment methods. The obtained results have demonstrated the validity of Absolute Category Rating (ACR) and Degradation Category Rating (DCR) for subjective tests with 360${^\circ }$videos, the possibility of using 10-second videos (with or without audio) when addressing quality evaluation of coding artifacts, as well as any commercial HMD (satisfying minimum requirements). Also, more efficient methods than the long Simulator Sickness Questionnaire (SSQ) have been proposed to evaluate related symptoms with 360${^\circ }$videos. These results have been instrumental for the development of the ITU-T Recommendation P.919. Finally, the annotated dataset from the tests is made publicly available for the research community.

Digital technology offers multimodal presentation of information, that can be used for translating foreign languages or for alleviating hearing impairment or deafness communication problems. Today, there exists various aids that can be used for speech-to text translations, but there are some challenges with these. One potential solution for this is to make use of a combination of Augmented Reality (AR) and speech-to-text systems, where speech is converted into text that is then presented in AR-glasses. In AR, one crucial problem is the legibility and readability of text under different environmental conditions. Different types of AR glasses have different ergonomic characteristics, which implies that certain glasses might be more suitable for such a system than others. In this investigation, two different AR-glasses were evaluated based on among other things their optical, visual, and ergonomic characteristics. User tests were conducted to evaluate the legibility and readability of text under different environmental contexts. The results indicate that legibility and readability are affected by factors such as ambient illuminance, background properties and how the text is presented with respect to polarity, opacity, size, and number of lines. The characteristics of the glasses impacts the user experience, but which glasses that is preferred depends on the individual.

In this article, we have investigated a VR simulator of a forestry crane used for loading logs onto a truck. We have mainly studied the Quality of Experience (QoE) aspects that may be relevant for task completion, and whether there are any discomfort related symptoms experienced during the task execution. QoE experiments were designed to capture the general subjective experience of using the simulator, and to study task performance. The focus was to study the effects of latency on the subjective experience, with regards to delays in the crane control interface. Subjective studies were performed with controlled delays added to the display update and hand controller (joystick) signals. The added delays ranged from 0 to 30 ms for the display update, and from 0 to 800 ms for the hand controller. We found a strong effect on latency in the display update and a significant negative effect for 800 ms added delay on latency in the hand controller (in total approx. 880 ms latency including the system delay). The Simulator Sickness Questionnaire (SSQ) gave significantly higher scores after the experiment compared to before the experiment, but a majority of the participants reported experiencing only minor symptoms. Some test subjects ceased the test before finishing due to their symptoms, particularly due to the added latency in the display update.

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.

Today's packet-switched networks are subject to bandwidth fluctuations that cause degradation of the user experience of multimedia services. In order to cope with this problem, HTTP adaptive streaming (HAS) has been proposed in recent years as a video delivery solution for the future Internet and being adopted by an increasing number of streaming services, such as Netflix and Youtube. HAS enables service providers to improve users' quality of experience (QoE) and network resource utilization by adapting the quality of the video stream to the current network conditions. However, the resulting time-varying video quality caused by adaptation introduces a new type of impairment and thus novel QoE research challenges. Despite various recent attempts to investigate these challenges, many fundamental questions regarding HAS perceptual performance are still open. In this paper, the QoE impact of different technical adaptation parameters, including chunk length, switching amplitude, switching frequency, and temporal recency, are investigated. In addition, the influence of content on perceptual quality of these parameters is analyzed. To this end, a large number of adaptation scenarios have been subjectively evaluated in four laboratory experiments and one crowdsourcing study. A statistical analysis of the combined data set reveals results that partly contradict widely held assumptions and provide novel insights in perceptual quality of adapted video sequences, e.g., interaction effects between quality switching direction (up/down) and switching strategy (smooth/abrupt). The large variety of experimental configurations across different studies ensures the consistency and external validity of the presented results that can be utilized for enhancing the perceptual performance of adaptive streaming services.

A tremendous number of objective video quality measurement algorithms have been developed during the last two decades. Most of them either measure a very limited aspect of the perceived video quality or they measure broad ranges of quality with limited prediction accuracy. This paper lists several perceptual artifacts that may be computationally measured in an isolated algorithm and some of the modeling approaches that have been proposed to predict the resulting quality from those algorithms. These algorithms usually have a very limited application scope but have been verified carefully. The paper continues with a review of some standardized and well-known video quality measurement algorithms that are meant for a wide range of applications, thus have a larger scope. Their individual artifacts prediction accuracy is usually lower but some of them were validated to perform sufficiently well for standardization. Several difficulties and shortcomings in developing a general purpose model with high prediction performance are identified such as a common objective quality scale or the behavior of individual indicators when confronted with stimuli that are out of their prediction scope. The paper concludes with a systematic framework approach to tackle the development of a hybrid video quality measurement in a joint research collaboration.

The free-form surface matching problem is important in several practical applications, such as reverse engineering. An accurate, robust and fast solution is, therefore, of great significance. Recently genetic algorithms have attracted great interest for their ability to robustly solve hard optimization problems. In this work we investigate the performance of such an approach for finding the initial guess of the transformation, a translation and a rotation, between the object and the model surface. This is followed by a local gradient descent method, such as iterative closest point, to refine the estimate. Promising results are demonstrated on accurate real data.

It is well-known that active selection of fixation points in humans is highly context and task dependent. It is therefore likely that successful computational processes for fixation in active vision should be so too. We are considering active fixation in the context of recognition of man-made objects characterized by their shapes. In this situation the qualitative shape and type of observed junctions play an important role. The fixations are driven by a grouping strategy, which forms sets of connected junctions separated from the surrounding at depth discontinuities. We have furthermore developed a methodology for rapid active detection and classification of junctions by selection of fixation points. The approach is based on direct computations from image data and allows integration of stereo and accommodation cues with luminance information. This work form a part of an effort to perform active recognition of generic objects, in the spirit of Malik and Biederman, but on real imagery rather than on line-drawings.