004 Datenverarbeitung; Informatik
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Natural walking in virtual reality games is constrained by the physical boundaries defined by the size of the player’s tracking space. Impossible spaces, a redirected walking technique, enlarge the virtual environment by creating overlapping architecture and letting multiple locations occupy the same physical space. Within certain thresholds, this is subtle to the player. In this paper, we present our approach to implement such impossible spaces and describe how we handled challenges like objects with simulated physics or precomputed global illumination.
Uplink vs. Downlink: Machine Learning-Based Quality Prediction for HTTP Adaptive Video Streaming
(2021)
Streaming video is responsible for the bulk of Internet traffic these days. For this reason, Internet providers and network operators try to make predictions and assessments about the streaming quality for an end user. Current monitoring solutions are based on a variety of different machine learning approaches. The challenge for providers and operators nowadays is that existing approaches require large amounts of data. In this work, the most relevant quality of experience metrics, i.e., the initial playback delay, the video streaming quality, video quality changes, and video rebuffering events, are examined using a voluminous data set of more than 13,000 YouTube video streaming runs that were collected with the native YouTube mobile app. Three Machine Learning models are developed and compared to estimate playback behavior based on uplink request information. The main focus has been on developing a lightweight approach using as few features and as little data as possible, while maintaining state-of-the-art performance.
In this paper, we bridge the gap between procedural content generation (PCG) and user-generated content (UGC) by proposing and demonstrating an interactive agent-based model of self-assembling ensembles that can be directed though user input. We motivate these efforts by considering the opportunities technology provides to pursue game designs based on according game design frameworks. We present three different use cases of the proposed model that emphasize its potential to (1) self-assemble into predefined 3D graphical assets, (2) define new structures in the context of virtual environments by self-assembling layers on the surfaces of arbitrary 3D objects, and (3) allow novel structures to self-assemble only considering the model’s configuration and no external dependencies. To address the performance restrictions in computer games, we realized the prototypical model implementation by means of an efficient entity component system (ECS). We conclude the paper with an outlook on future steps to further explore novel interactive, dynamic PCG mechanics and to ensure their efficiency.
Measurements of physiological parameters provide an objective, often non-intrusive, and (at least semi-)automatic evaluation and utilization of user behavior. In addition, specific hardware devices of Virtual Reality (VR) often ship with built-in sensors, i.e. eye-tracking and movements sensors. Hence, the combination of physiological measurements and VR applications seems promising. Several approaches have investigated the applicability and benefits of this combination for various fields of applications. However, the range of possible application fields, coupled with potentially useful and beneficial physiological parameters, types of sensor, target variables and factors, and analysis approaches and techniques is manifold. This article provides a systematic overview and an extensive state-of-the-art review of the usage of physiological measurements in VR. We identified 1,119 works that make use of physiological measurements in VR. Within these, we identified 32 approaches that focus on the classification of characteristics of experience, common in VR applications. The first part of this review categorizes the 1,119 works by field of application, i.e. therapy, training, entertainment, and communication and interaction, as well as by the specific target factors and variables measured by the physiological parameters. An additional category summarizes general VR approaches applicable to all specific fields of application since they target typical VR qualities. In the second part of this review, we analyze the target factors and variables regarding the respective methods used for an automatic analysis and, potentially, classification. For example, we highlight which measurement setups have been proven to be sensitive enough to distinguish different levels of arousal, valence, anxiety, stress, or cognitive workload in the virtual realm. This work may prove useful for all researchers wanting to use physiological data in VR and who want to have a good overview of prior approaches taken, their benefits and potential drawbacks.
Having a mixed-cultural membership becomes increasingly common in our modern society. It is thus beneficial in several ways to create Intelligent Virtual Agents (IVAs) that reflect a mixed-cultural background as well, e.g., for educational settings. For research with such IVAs, it is essential that they are classified as non-native by members of a target culture. In this paper, we focus on variations of IVAs’ speech to create the impression of non-native speakers that are identified as such by speakers of two different mother tongues. In particular, we investigate grammatical mistakes and identify thresholds beyond which the agents is clearly categorised as a non-native speaker. Therefore, we conducted two experiments: one for native speakers of German, and one for native speakers of English. Results of the German study indicate that beyond 10% of word order mistakes and 25% of infinitive mistakes German-speaking IVAs are perceived as non-native speakers. Results of the English study indicate that beyond 50% of omission mistakes and 50% of infinitive mistakes English-speaking IVAs are perceived as non-native speakers. We believe these thresholds constitute helpful guidelines for computational approaches of non-native speaker generation, simplifying research with IVAs in mixed-cultural settings.
Crowdsourced network measurements (CNMs) are becoming increasingly popular as they assess the performance of a mobile network from the end user's perspective on a large scale. Here, network measurements are performed directly on the end-users' devices, thus taking advantage of the real-world conditions end-users encounter. However, this type of uncontrolled measurement raises questions about its validity and reliability. The problem lies in the nature of this type of data collection. In CNMs, mobile network subscribers are involved to a large extent in the measurement process, and collect data themselves for the operator. The collection of data on user devices in arbitrary locations and at uncontrolled times requires means to ensure validity and reliability. To address this issue, our paper defines concepts and guidelines for analyzing the precision of CNMs; specifically, the number of measurements required to make valid statements. In addition to the formal definition of the aspect, we illustrate the problem and use an extensive sample data set to show possible assessment approaches. This data set consists of more than 20.4 million crowdsourced mobile measurements from across France, measured by a commercial data provider.
Mindfulness is considered an important factor of an individual's subjective well-being. Consequently, Human-Computer Interaction (HCI) has investigated approaches that strengthen mindfulness, i.e., by inventing multimedia technologies to support mindfulness meditation. These approaches often use smartphones, tablets, or consumer-grade desktop systems to allow everyday usage in users' private lives or in the scope of organized therapies. Virtual, Augmented, and Mixed Reality (VR, AR, MR; in short: XR) significantly extend the design space for such approaches. XR covers a wide range of potential sensory stimulation, perceptive and cognitive manipulations, content presentation, interaction, and agency. These facilities are linked to typical XR-specific perceptions that are conceptually closely related to mindfulness research, such as (virtual) presence and (virtual) embodiment. However, a successful exploitation of XR that strengthens mindfulness requires a systematic analysis of the potential interrelation and influencing mechanisms between XR technology, its properties, factors, and phenomena and existing models and theories of the construct of mindfulness. This article reports such a systematic analysis of XR-related research from HCI and life sciences to determine the extent to which existing research frameworks on HCI and mindfulness can be applied to XR technologies, the potential of XR technologies to support mindfulness, and open research gaps. Fifty papers of ACM Digital Library and National Institutes of Health's National Library of Medicine (PubMed) with and without empirical efficacy evaluation were included in our analysis. The results reveal that at the current time, empirical research on XR-based mindfulness support mainly focuses on therapy and therapeutic outcomes. Furthermore, most of the currently investigated XR-supported mindfulness interactions are limited to vocally guided meditations within nature-inspired virtual environments. While an analysis of empirical research on those systems did not reveal differences in mindfulness compared to non-mediated mindfulness practices, various design proposals illustrate that XR has the potential to provide interactive and body-based innovations for mindfulness practice. We propose a structured approach for future work to specify and further explore the potential of XR as mindfulness-support. The resulting framework provides design guidelines for XR-based mindfulness support based on the elements and psychological mechanisms of XR interactions.
Psycho-pathological conditions, such as depression or schizophrenia, are often accompanied by a distorted perception of time. People suffering from this conditions often report that the passage of time slows down considerably and that they are “stuck in time.” Virtual Reality (VR) could potentially help to diagnose and maybe treat such mental conditions. However, the conditions in which a VR simulation could correctly diagnose a time perception deviation are still unknown. In this paper, we present an experiment investigating the difference in time experience with and without a virtual body in VR, also known as avatar. The process of substituting a person’s body with a virtual body is called avatar embodiment. Numerous studies demonstrated interesting perceptual, emotional, behavioral, and psychological effects caused by avatar embodiment. However, the relations between time perception and avatar embodiment are still unclear. Whether or not the presence or absence of an avatar is already influencing time perception is still open to question. Therefore, we conducted a between-subjects design with and without avatar embodiment as well as a real condition (avatar vs. no-avatar vs. real). A group of 105 healthy subjects had to wait for seven and a half minutes in a room without any distractors (e.g., no window, magazine, people, decoration) or time indicators (e.g., clocks, sunlight). The virtual environment replicates the real physical environment. Participants were unaware that they will be asked to estimate their waiting time duration as well as describing their experience of the passage of time at a later stage. Our main finding shows that the presence of an avatar is leading to a significantly faster perceived passage of time. It seems to be promising to integrate avatar embodiment in future VR time-based therapy applications as they potentially could modulate a user’s perception of the passage of time. We also found no significant difference in time perception between the real and the VR conditions (avatar, no-avatar), but further research is needed to better understand this outcome.
To deliver the best user experience (UX), the human-centered design cycle (HCDC) serves as a well-established guideline to application developers. However, it does not yet cover network-specific requirements, which become increasingly crucial, as most applications deliver experience over the Internet. The missing network-centric view is provided by Quality of Experience (QoE), which could team up with UX towards an improved overall experience. By considering QoE aspects during the development process, it can be achieved that applications become network-aware by design. In this paper, the Quality of Experience Centered Design Cycle (QoE-CDC) is proposed, which provides guidelines on how to design applications with respect to network-specific requirements and QoE. Its practical value is showcased for popular application types and validated by outlining the design of a new smartphone application. We show that combining HCDC and QoE-CDC will result in an application design, which reaches a high UX and avoids QoE degradation.
As part of the Clash of Realities International Conference on the Technology and Theory of Digital Games, the Game Technology Summit is a premium venue to bring together experts from academia and industry to disseminate state-of-the-art research on trending technology topics in digital games. In this first iteration of the Game Technology Summit, we specifically paid attention on how the successes in AI in Natural User Interfaces have been impacting the games industry (industry track) and which scientific, state-of-the-art ideas and approaches are currently pursued (scientific track).