Cold temperature negatively impacts the performance of liquid crystal displays (LCDs). In cars, this leads to slow response times and reduced image quality. We investigated how the perception of video distortions on LCD screens was affected by cold temperatures down to −43°C. The stimuli were generated using digital filters simulating how different time constants of the LCD crystals would affect the video distortions. Seven levels of time constants were applied to four variations of video content. Simulated videos were shown in a psychophysical experiment involving 20 test persons. Judgements of video clarity and acceptance were conducted by magnitude estimation and category scales. The two different judgements based on magnitude estimations and psychophysical scales gave similar results. Clarity and acceptance correlated. A modified Arrhenius function was employed to model time constants based on temperature, showing unacceptable quality of the LCD-display below –20°C. The traffic scenes were perceived as clear and acceptable with time constants ranging from 0 and 50 ms. The critical range between 50 to 100 ms corresponded to a temperature range between –20°C to –30°C, beyond which clarity and acceptance decreased. Perception of an unacceptable video quality was found for distortions at time constants between 100 to 500 ms

Digital camera-based rear‑view systems are increasingly introduced as alternatives to traditional mirrors, offering potential benefits such as improved aerodynamics, reduced blind spots, and enhanced visibility. However, these systems alter the visual cues available to drivers by presenting a fixed monocular image, which might affect how distance and approach speed are judged. This study examines how driver-age influences distance estimation and decisions related to overtaking, while also assessing the impact of camera field of view and camera height. Fifty‑eight licensed car drivers viewed thirty‑six high‑resolution driving clips showing forward‑road scenes and digital rear‑view perspectives with systematically varied camera settings. They completed two tasks: judging the distance of an approaching vehicle and indicating the last moment at which a lane change would be considered safe. Age influenced both perceptual judgements and lane‑change decisions, though not always in the expected direction. Older drivers showed smaller overall errors, yet at wider fields of view they often shifted into overestimation, while younger drivers maintained conservative underestimation. Older drivers nevertheless selected more cautious lane‑change timings in certain conditions. Apparent accuracy advantages may reflect reduced bias rather than consistently safer perception; The results highlight the importance of accounting for user diversity when evaluating camera-based rear‑view systems and developing age‑inclusive design strategies.

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.

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. 

A well-known drawback with LCD-displays in cold is a slow pixel response leading to poor picture quality. Low temperatures can constitute a hazard in viewing important displays in cars. Perceptual experiments with 20 test-persons were conducted to find clear and acceptable ranges on screens simulating distortions in low temperatures. The results showed perception over clear and acceptable image quality was impaired beyond -20°C for the LCD-screen in the experiments. 

Changes in the footballing world’s approach to technology and innovation contributed to the decision by the International Football Association Board to introduce Video Assistant Referees (VAR). The change meant that under strict protocols referees could use video replays to review decisions in the event of a "clear and obvious error" or a "serious missed incident". This led to the need by Fédération Internationale de Football Association (FIFA) to develop methods for quality control of the VAR-systems, which was done in collaboration with RISE Research Institutes of Sweden AB. One of the important aspects is the video quality. The novelty of this study is that it has performed a user study specifically targeting video experts i.e., to measure the perceived quality of video professionals working with video production as their main occupation. An experiment was performed involving 25 video experts. In addition, six video quality models have been benchmarked against the user data and evaluated to show which of the models could provide the best predictions of perceived quality for this application. Video Quality Metric for variable frame delay (VQM_VFD) had the best performance for both formats, followed by Video Multimethod Assessment Fusion (VMAF) and VQM General model.

Att ha en hörselskada eller att vara döv har flera konsekvenser på individens livskvalité. Det påverkar vardagen i stor utsträckning och gör det svårt att delta i konversationer. Det finns redan flera hjälpmedel för att underlätta vardagen för individer med hörselskador, exempelvis  hörapparater. Dock finns vissa utmaningar och problem med dessa. En möjlig lösning skulle kunna vara att använda Augmented Reality, eller förstärkt verklighet tillsammans med ett tal-till-text-system, där tal skulle kunna konverteras til text som exempelvis presenteras i AR-glasögon. Augmented Reality (AR) är en teknik som möjliggör att förstärka verkligheten genom att  datorgenerande information, till exempel visuella objekt, presenteras ovanpå verkligheten. En variant av en AR-teknologi är AR-glasögon, vilket innebär att datorgenerade objekt presenteras i glasögonen och sedermera förstärker användarens verklighet. Olika varianter av AR och AR-glasögon har studerats länge, men det inte förrän under den senaste tiden som kvalitén blivit tillräckligt bra för att kunna användas i vardagen. Idag finns flera olika AR-glasögon, med olika tekniska, ergonomiska, visuella och optiska egenskaper, där vissa glasögon kan vara mer eller mindre lämpade inom ett visst användningsområde. Glasögonens egenskaper påverkar även användarens upplevelse. Även om tekniken redan finns på marknaden kvarstår vissa problem, exempelvis belysning, bakgrund och att synligheten av de datorgenerade objekten påverkas av förhållanden i omgivningen. Då målet är att presentera text i AR-glasögonen är det viktiga att texten är synlig, läslig1 och läsbar2 under flera olika förhållanden, som varierande belysning och bakgrund. Dessutom bör hänsyn tas till hur texten presenteras, där faktorer som storlek, textfärg, bakgrundsfärg bakom text samt antal rader bör beaktas. Tal-till-text-system är också en teknik som fått genomslag under de senaste åren. Bland annat tack vare de stora framsteg som gjorts inom taligenkänning. På den engelskspråkiga marknaden är tekniken utbredd och det finns flera befintliga system, som Google Cloud Speech API, IBM Watson och Microsoft Azure. På den svenska marknaden finns dock få system och utvärderingar av dessa. Vid utvärderingar av tal-till-text-system bör man ta hänsyn till faktorer som korrekthet, fördröjning och robusthet under olika ljudnivåer, talhastigheter och dialekter. Således bör man utvärdera vilket svenskt tal-till-text-system som är lämpligast att använda för att översätta tal till text med hänsyn till ovannämnda aspekter. I detta examensarbete undersöks hur egenskaperna i två olika AR-glasögon påverkar användarupplevelsen med fokus på komfort, design, samt glasögonens optiska och visuella egenskaper. Vidare undersöks hur belysning och bakgrund påverkar läsligheten och läsbarheten av text, samt hur texten ska presenteras för att resultera i bäst läslighet och läsbarhet. Detta studeras genom användartester, där olika formateringar på texten presenteras under olika belysningar och med olika bakgrund. Detta följs av en kort enkät där deltagarna får besvara frågor gällande textformateringarna. Enkäten innehåller även frågor relaterade till glasögonens egenskaper och hur dessa påverkar användarupplevelsen för att kunna undersöka vilka glasögon som skulle vara mest lämpade för detföreslagna systemet. Avslutande genomförs en marknadsundersökning och litteraturundersökning över befintliga tal-till-text-system på den svenska marknaden. Resultatet från studien visar att belysning och bakgrund påverkar synligheten och sedermera läsligheten av texten som presenteras i glasögonen. Vidare påvisas det att textens formatering, med avseende på textfärg, textbakgrund, antal rader och storlek påverkar läsligheten. Resultatet visar även att AR-glasögonens egenskaper påverkar användarupplevelsen, läsligheten och läsbarheten. Vilka glasögon som är bäst lämpade tycks dock bero på individuella preferenser. Gällande tal-till-text-system, indentifieras fyra stycken som finns tillgängliga på den svenska marknaden. Utifrån utvärderingen av tillgängliga tal-till-text-system rekommenderas Google Cloud Speech API, baserat på tekniska egenskaper, robusthet och tillgänglighet.

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.

This report describes the work and conclusions drawn after phase 4 in the project “Assessment methods for Video assistant refereeing (VAR) System”.

The performance of six different video quality models have been evaluated, that were identified during phase 1, against the subjective video quality database that was created during phase 3. The results are slightly different for 1080p compared to 1080i. For 1080p the models VQM_VFD, SSIM and VMAF performs the best with Pearson Correlation Coefficients (PCC) above 0.9. For 1080i the PCC drops a bit overall and then VMAF and VQM_VFD are close in performance and performing the best. The overall performance for both formats VMAF an VQM_VFD stands out as the best models. In this comparison VQM_VFD has the added advantage to also be able to perform its own registration i.e. to fix any misalignment between the reference video and the distorted one.

This report describes the work and conclusions drawn after phase 4 for the synchronization and latencymeasurements in the project “Assessment methods for Video Assistant Refereeing (VAR) System”.In phase 4, we have focused on up-dating the software so that it automatically detects: p (progressive),i (interlaced), and PsF (progressive segmented frame) formats and analyse the different video types. Wehave also the performed a field-test with an OB-van at an arena.