Content Format and Quality of Experience in Virtual Reality

In this paper, we investigate three forms of virtual reality content production and consumption. Namely, 360 stereoscopic video, the combination of a 3D environment with a video billboard for dynamic elements, and a full 3D rendered scene. On one hand, video based techniques facilitate the acquisition of content, but they can limit the experience of the user since the content is captured from a fixed point of view. On the other hand, 3D content allows for point of view translation, but real-time photorealistic rendering is not trivial and comes at high production and processing costs. We also compare the two extremes with an approach that combines dynamic video elements with a 3D virtual environment. We discuss the advantages and disadvantages of these systems, and present the result of a user study with 24 participants. In the study, we evaluated the quality of experience, including presence, simulation sickness and participants' assessment of content quality, of three versions of a cinematic segment with two actors. We found that, in this context, mixing video and 3D content produced the best experience.Comment: 25 page

Crowdsourcing design guidance for contextual adaptation of text content in augmented reality

Funding Information: This work was supported by EPSRC (grants EP/R004471/1 and EP/S027432/1). Supporting data for this publication is available at https://doi.org/10.17863/CAM.62931.Augmented Reality (AR) can deliver engaging user experiences that seamlessly meld virtual content with the physical environment. However, building such experiences is challenging due to the developer's inability to assess how uncontrolled deployment contexts may infuence the user experience. To address this issue, we demonstrate a method for rapidly conducting AR experiments and real-world data collection in the user's own physical environment using a privacy-conscious mobile web application. The approach leverages the large number of distinct user contexts accessible through crowdsourcing to efciently source diverse context and perceptual preference data. The insights gathered through this method complement emerging design guidance and sample-limited lab-based studies. The utility of the method is illustrated by reexamining the design challenge of adapting AR text content to the user's environment. Finally, we demonstrate how gathered design insight can be operationalized to provide adaptive text content functionality in an AR headset.Publisher PD

A novel Big Data analytics and intelligent technique to predict driver's intent

Modern age offers a great potential for automatically predicting the driver's intent through the increasing miniaturization of computing technologies, rapid advancements in communication technologies and continuous connectivity of heterogeneous smart objects. Inside the cabin and engine of modern cars, dedicated computer systems need to possess the ability to exploit the wealth of information generated by heterogeneous data sources with different contextual and conceptual representations. Processing and utilizing this diverse and voluminous data, involves many challenges concerning the design of the computational technique used to perform this task. In this paper, we investigate the various data sources available in the car and the surrounding environment, which can be utilized as inputs in order to predict driver's intent and behavior. As part of investigating these potential data sources, we conducted experiments on e-calendars for a large number of employees, and have reviewed a number of available geo referencing systems. Through the results of a statistical analysis and by computing location recognition accuracy results, we explored in detail the potential utilization of calendar location data to detect the driver's intentions. In order to exploit the numerous diverse data inputs available in modern vehicles, we investigate the suitability of different Computational Intelligence (CI) techniques, and propose a novel fuzzy computational modelling methodology. Finally, we outline the impact of applying advanced CI and Big Data analytics techniques in modern vehicles on the driver and society in general, and discuss ethical and legal issues arising from the deployment of intelligent self-learning cars

Exposure to Gambling-Related Media and its Relation to Gambling Expectancies and Behaviors

Today’s youth have been exposed to more gambling-related media than previous generations, and they have grown up in an era in which states not only sanction but also run and promote gambling enterprises. Social Learning Theory proposes that one can develop new attitudes or expectancies about a specific behavior by watching others engage in that behavior, and that the media is one avenue through which one can develop new expectancies (Bandura, 2001). In addition, the Theory of Reasoned Action proposes that one’s behaviors are influenced directly by both subjective norms and attitudes (Fishbein and Ajzen, 1975). A mixed methods explanatory design was used to test a modified version of the Theory of Reasoned Action in which subjective norms and gambling-related media were hypothesized to have an effect on gambling behaviors directly and indirectly through both positive and negative expectancies. Structural Equation Modeling was used to test the hypotheses, and semi-standardized interviews were used to help explain the results of the quantitative analyses and provide a richer and more accurate interpretation of the data. The hypothesized model was partially supported: the model was a good fit with the female college student data, accounting for 27.8% of variance in female student gambling behaviors, and it fit the male college student data reasonably well, accounting for 35.2% of variance in male student gambling behaviors. Results indicated that perceived subjective norms were more important for female college students. Results also indicated that exposure to gambling-related media has a direct positive association with both male and female college student gambling behaviors, and that exposure to gambling-related media has an indirect, positive association with male college student behaviors through positive expectancies. However, exposure to gambling-related media is not associated with positive expectancies about gambling for female college students. Data from the qualitative interviews supported the findings from the qualitative analyses and provided some clues about the progression from non-problematic to problematic behaviors, which may inform future research in this area

The visual analysis of heterogeneous sex role interactions: a content analysis of popular music videos

Hip Hop cultured music videos have raised concern among our nation’s leaders, parents and communities. Since the introduction of music videos in the early 1980s the medium has crossed cultural, regional and ethnic boundaries (Rose, 1994). This medium has been well researched since the 1980s. The focus of this study is Hip Hop cultured music videos from years 1989-2006. The uniqueness of this study is that it focuses on nonverbal sex role interactions in this genre of music videos. This study found many useful trends. For example, men were portrayed as more dominant and/or vertical than women in the sampled music videos