Mid Sweden University

As the automotive industry becomes increasingly digitalized, Camera Monitoring Systems (CMS) are replacing traditional mirrors, offering improved aerodynamics and wider fields of view. However, depth perception remains a challenge, and unclear overlays can reduce driver trust. This study investigates how different CMS augmentations affect distance estimation during overtaking. Thirty participants viewed video clips across three road scenes using one baseline and three augmented interface concepts. They estimated vehicle distances, rated certainty, and reported preferences. The Lines concept, using distance lines and vehicle outlines, produced the most favorable results with the lowest absolute errors and highest clarity and reliability ratings, although it introduced systematic overestimation. The Corner concept led to consistent underestimation but offered some perceived benefits, while the Dashed concept performed similarly to the baseline. The final design builds on the strengths of the Lines concept, with refinements inspired by Corner to enhance visibility and stability. Recommendations include using intuitive depth cues, accessible colors, and well-timed visual elements. Future research should explore sound cues, symbolic warnings, and long-term user acceptance. 

This study explores how video quality, field of view, and latency influence users' performance, depth perception, and overall experience in remote-control systems for industrial teleoperated applications. In this controlled laboratory investi-gation, we conducted an experimental study using a test setup that closelyreplicated real-world conditions while ensuring experimental control and safety. Participants completed 18 trials under varying fields of view (Wide vs. Narrow), latency (High, Medium, Low), and video quality (High, Medium, Low)conditions to evaluate their navigation accuracy, depth perception and Qualityof Experience. Using a mixed-methods approach, considering Quality of Experience and User Experience insights, we integrated objective performance metrics, quantitative user evaluations, and qualitative feedback to understand how visual constraints impact control and decision-making. The results show that latency had the most impact on navigation accuracy, followed by field of view. The high latency level significantly influenced performance, caused larger deviations from the intended path, and reduced confidence in estimating depth. The effect was even more pronounced in narrow fields of view, where high latency further amplified navigation difficulties. In contrast, a wider field of view helped mitigate latency effects by improving situational awareness and reducing reliance on secondary visual cues. While video quality had minimal impact on objectivenavigation performance, qualitative feedback indicated that higher video quality improved confidence in depth perception and reduced visual strain, supporting users in making precise judgments. We also collected users' feedback that provided cues to further enhance the teleoperation systems

The International Telecommunication Union has a project for developing objective quality models called Parametric Bitstream-Based Quality Assessment of Cloud Gaming services. The model will be divided into an interaction quality module and a video coding impairment module. To evaluate these two modules an experimental campaign was conducted where labs from different parts of the world performed user studies to collect data for the evaluation. This paper describes an experiment for collecting data to evaluate the video coding impairment module. The analysis is based on a bootstrapping approach. 

This study investigates how different camera perspectives presented in digital rear-view mirrors in vehicles, also known as Camera Monitor Systems, impact drivers’ distance judgment and decision-making in dynamic driving scenarios. The study examines (1) the effects of field of view and (2) camera height on drivers' ability to judge distances to rearward vehicles and to select safe gaps in potentially hazardous situations. A controlled lab-based video experiment was conducted, involving 27 participants who performed distance estimations and last safe gap selections using a simulated side-view mirror display. Participants viewed prerecorded driving scenarios with varying combinations of field of view (40°, 76°, 112°) and camera heights (1 meter, 2.3 meter). No significant effects were found for camera height, but wider field of views led to more accurate distance estimations. However, the use of a wider field of view also increased the risk of potentially dangerous overestimations of distance, as evidenced by the last safe gap results. This suggests that a wider field of view leads to the selection of smaller and potentially risky gaps. Conversely, narrow field of views resulted in underestimations of distance, potentially leading to overly cautious and less efficient driving decisions. These findings inform Camera Monitor Systems design guidelines on how to improve driver perception and road safety, to reduce accidents from vehicle distance misjudgments. 

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.

Recently, the traditional rear and side view mirrors have been started to be exchanged with a digital version. The aim of this study was to investigate the difference in driving performance between traditional rear-view mirrors and digital rear view mirrors which is called Camera Monitor System (CMS) in the vehicle industry. Here, two different types were investigated: CMS without or with Augmented Reality (AR) Information. The user test was conducted in a virtual environment, with four driving scenarios defined for testing. The user test results revealed that the participants' driving performance using CMS (only cameras and 2D displays without augmented information) did not improve over traditional mirrors. 

Thanks to the advent of telepresence applications, we can remotely take control and operate industrial machinery. Teleoperation removes operators from hazardous workplaces such asmining and plays an essential role in the safety of workers. In addition, augmented telepresence can introduce information that helps the user understand the remote scene. However, remote operation has challenges when the received information is more limited than what could be perceived on-site–e.g., judging depth. This study investigates how well operators interact with an Augmented Remote Operation Scaling System (AROSS) in a mining context when different computer-generated visual interfaces are provided. The system can achieve five augmented views: Disocclusion Augmentation using selective content removal; Novel Perspective view generation; Lidar view; Right field of view; and Left field of view. We performed two experiments in a mine-like laboratory. The first experiment was a feasibility test to obtain an understanding of what users need to accurately perceive depth. The second experiment was designed to evaluate the user’s experience with the different versions of AROSS. To analyze human interaction with the designed prototype, we employed a mixed research methodology that used interviews, observations, and questionnaires. This mixed methodology consisted of quality of experience methods to discover the users’requirements from a technological standpoint and user experience methods (i.e., user-centricapproaches). We investigated 10 and 11 users’ interactions in the two subjective experiments. The first experiment focused on the effects of in-view augmentations and interface distributions on perceiving wall patterns. The second focused on the effects of augmentations on the depth and understanding the 3D environment. Using these data, we analyzed both thequality of experience and user experience via evaluation criteria consisting of interface helpfulness, task performance, potential improvement, and user satisfaction. The feasibility test results were mainly used to structure the formative investigation. The overall conclusion from the formative testing shows that the remote operators preferred using natural views (Original) as this approach made it easier to understand the environment. Although the augmented computer-generated views do not look natural, they support 3D cues. In addition, the combination of Novel Perspective and Lidar interfaces as additional views in depth perception tasks seemed helpful. There was difficulty performing tasks when the robot arm was obscured during the Disocclusion Augmentation view and low video quality during the Novel Perspective view. However, participants found the Novel Perspective view useful for geometry and depth estimation.

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. 

In this study, we designed an experiment using remote-controlled lab based moving platform to evaluate the impact of resolution, latency, and field of view on the Quality of Experience, performance, user experience and depth perception. The experiment involves two tasks: driving the platform to a stop point and parking it between two boxes. Participants provided feedback through questionnaires, and their experiences were analyzed. Seven participants between 30 and 57 (average of 37) years old participated. We used Google Forms for data collection, including pre-experiment and recurring questionnaires as well as a simulator sickness questionnaire. Despite the low number of test participants leading to uncertainty in quantitative analysis, significant effects were observed, albeit with contradictory statistical outcomes. The data suggests that lower latency corresponds to better performance, with participants not always perceiving higher latency accurately. Video quality notably impacts user experience, with higher resolution being preferred.

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.