When visualizing large datasets, an important goal is to emphasize data that is relevant to the task at hand. A common way of achieving this is to compute the relevance of the data using degree of interest (DOI) funct...
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ISBN:
(纸本)9798350325577
When visualizing large datasets, an important goal is to emphasize data that is relevant to the task at hand. A common way of achieving this is to compute the relevance of the data using degree of interest (DOI) functions, which apply a scenario-specific metric to quantify the data items according to their relevance to the users and their tasks. These DOI values can then be used to adjust the visual encoding through mechanisms like focus+context or information hiding. For datasets too large to be visualized at once, an alternative approach is to visualize it progressively in chunks, allowing analysts to reason about partial results and concluding their analysis much earlier than had they waited for all data. Combining the advantages of both approaches to tailor the visualization seems synergistic, yet, in practice turns out to be challenging, as DOI functions require the context of all data to produce useful values, requiring lengthy computations that break analysts' flow in progressive visualization. In this paper, we propose an approach for uniting DOI functions with progressive visualization. We first introduce a new model for quantifying the user interest in analysis scenarios where the data is only partially available, by computing the interest for available data and predicting it for the rest. We then propose regression trees for implementing this approach in practice and evaluate it in benchmarks. With DOI values now available for progressive visualization as well, our approach opens the door for tailoring the visualization of large datasets to the analysis task at interactive update rates.
Limited mobility in augmented reality applications restricts spatial understanding along with augmentation placement and visibility. Systems can counteract by providing perspectives by tracking and augmenting mirrors ...
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ISBN:
(纸本)9798350348392
Limited mobility in augmented reality applications restricts spatial understanding along with augmentation placement and visibility. Systems can counteract by providing perspectives by tracking and augmenting mirrors without requiring user movement. However, the decreased visual size of mirrored objects reduces accuracy for precision tasks. We propose Magnifying Augmented Mirrors: digitally zoomed mirror images mapped hack onto their surface, producing magnified reflections. In a user study (N = 14) conducted in virtual reality, we evaluated our method on a precision alignment task. Although participants needed time for acclimatization, they achieved the most accurate results using a magnified mirror.
The majority of music consumption nowadays takes place on music streaming platforms. Whichever artists, albums, or songs are exposed to consumers on these platforms therefore greatly influences what music is ultimatel...
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ISBN:
(纸本)9781450399326
The majority of music consumption nowadays takes place on music streaming platforms. Whichever artists, albums, or songs are exposed to consumers on these platforms therefore greatly influences what music is ultimately consumed. As a result, the impact of these platforms on artists-their main item providers-is considerable. The recommender systems at the core of streaming platforms, though, have traditionally been developed focusing on end consumer objectives. Only recently, researchers have started to include item provider objectives, though rarely through reaching out to item providers directly. By omitting this important stakeholder's point of view, we risk not understanding what artists value most, and might miss first-hand ideas on how to improve streaming platforms and recommender systems. Therefore, we conducted semi-structured interviews to capture the artists' view. Specifically, we explore artists' considerations regarding fairness, transparency, and diversity in music recommender systems, and the role artists envision for streaming platforms regarding those topics. We identify some topics with a clear consensus among artists, such as desiring more control over which music is recommended to whom, and expecting streaming platforms to actively increase music diversity in recommendations. In contrast, artists' opinions differ on whether platforms should actively intervene in recommender systems to, e.g., increase localization or gender balance. Further, we observe that artists often take user preferences into account and even suggest new platform functionality to benefit both users and item providers. We encourage utilizing these insights when designing and evaluating music streaming platforms and recommender systems.
Virtual reality (VR) produces a highly realistic simulated environment with controllable environment variables. This paper proposes a Dynamic Scene Adjustment (DSA) mechanism based on the user interaction status and p...
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ISBN:
(纸本)9798350348392
Virtual reality (VR) produces a highly realistic simulated environment with controllable environment variables. This paper proposes a Dynamic Scene Adjustment (DSA) mechanism based on the user interaction status and performance, which aims to adjust the VR experiment variables to improve the user's game engagement. We combined the DSA mechanism with a musical rhythm VR game. The experimental results show that the DSA mechanism can improve the user's game engagement (task performance).
Widespread adoption of virtual reality (VR) will likely be limited by the common occurrence of cybersickness. Cybersickness susceptibility varies across individuals, and previous research reported that interpupillary ...
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ISBN:
(纸本)9798350348392
Widespread adoption of virtual reality (VR) will likely be limited by the common occurrence of cybersickness. Cybersickness susceptibility varies across individuals, and previous research reported that interpupillary distance (IPD) may be a factor. However, that work emphasized cybersickness recovery rather than cybersickness immediately after exposure. The current study (N=178) examined if the mismatch between the user's IPD and the VR headset's IPD setting contributes to immediate cybersickness. Multiple linear regression indicated that gender and prior sickness due to screens were significant predictors of immediate cybersickness. However, no significant relationship between IPD mismatch and immediate cybersickness was observed.
With the rise of the metaverse, more and more massively multi-user applications are to be expected. Because some of the data integrated in those virtual environments can be seen as highly sensitive, it is important to...
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ISBN:
(纸本)9798350348392
With the rise of the metaverse, more and more massively multi-user applications are to be expected. Because some of the data integrated in those virtual environments can be seen as highly sensitive, it is important to reinforce the applications with authentication methods to keep them safe. However, and while there are many authentication methods for 2D applications that could be regarded as safe enough, most of them do not provide a sufficient ease of use for VR applications. Henceforth, we propose an authentication method adapted to 3D user interfaces, based on toggling areas in a cubic grid. As illustrated in Figure 1, this leads to the construction of a voxelbased volume, which is an object simple enough to remember and playful to build, yet difficult to guess thanks to a high number of possibilities. For a more portable authentication method, the cubic grid is complemented by the generation of virtual keys representing the access a user has to a certain lock. The key acts as a metaphor that allows to easily share or grant access to secured objects or places in the VE.
Dimensionality reduction (DR) techniques inherently distort the original structure of input high-dimensional data, producing imperfect low-dimensional embeddings. Diverse distortion measures have thus been proposed to...
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ISBN:
(纸本)9798350325577
Dimensionality reduction (DR) techniques inherently distort the original structure of input high-dimensional data, producing imperfect low-dimensional embeddings. Diverse distortion measures have thus been proposed to evaluate the reliability of DR embeddings. However, implementing and executing distortion measures in practice has so far been time-consuming and tedious. To address this issue, we present ZADU, a Python library that provides distortion measures. ZADU is not only easy to install and execute but also enables comprehensive evaluation of DR embeddings through three key features. First, the library covers a wide range of distortion measures. Second, it automatically optimizes the execution of distortion measures, substantially reducing the running time required to execute multiple measures. Last, the library informs how individual points contribute to the overall distortions, facilitating the detailed analysis of DR embeddings. By simulating a real-world scenario of optimizing DR embeddings, we verify that our optimization scheme substantially reduces the time required to execute distortion measures. Finally, as an application of ZADU, we present another library called ZADUVis that allows users to easily create distortion visualizations that depict the extent to which each region of an embedding suffers from distortions.
Virtual avatars are more and more often featured in Virtual Reality (VR) and Augmented Reality (AR) applications. When embodying a virtual avatar, one may desire to change of appearance over the course of the embodime...
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ISBN:
(纸本)9798350348156
Virtual avatars are more and more often featured in Virtual Reality (VR) and Augmented Reality (AR) applications. When embodying a virtual avatar, one may desire to change of appearance over the course of the embodiment. However, switching suddenly from one appearance to another can break the continuity of the user experience and potentially impact the sense of embodiment (SoE), especially when the new appearance is very different. In this paper, we explore how applying smooth visual transitions at the moment of the change can help to maintain the SoE and benefit the general user experience. To address this, we implemented an AR system allowing users to embody a regular-shaped avatar that can be transformed into a muscular one through a visual effect. The avatar's transformation can be triggered either by the user through physical action ("active" transition), or automatically launched by the system ("passive" transition). We conducted a user study to evaluate the effects of these two types of transformations on the SoE by comparing them to control conditions where there was no visual feedback of the transformation. Our results show that changing the appearance of one's avatar with an active transition (with visual feedback), compared to a passive transition, helps to maintain the user's sense of agency, a component of the SoE. They also partially suggest that the Proteus effects experienced during the embodiment were enhanced by these transitions. Therefore, we conclude that visual effects controlled by the user when changing their avatar's appearance can benefit their experience by preserving the SoE and intensifying the Proteus effects.
The expression of human emotion is integral to social interaction, and in virtual reality it is increasingly common to develop virtual avatars that attempt to convey emotions by mimicking these visual and aural cues, ...
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ISBN:
(纸本)9798350348156
The expression of human emotion is integral to social interaction, and in virtual reality it is increasingly common to develop virtual avatars that attempt to convey emotions by mimicking these visual and aural cues, i.e. the facial and vocal expressions. However, errors in (or the absence of) facial tracking can result in the rendering of incorrect facial expressions on these virtual avatars. For example, a virtual avatar may speak with a happy or unhappy vocal inflection while their facial expression remains otherwise neutral. In circumstances where there is conflict between the avatar's facial and vocal expressions, it is possible that users will incorrectly interpret the avatar's emotion, which may have unintended consequences in terms of social influence or in terms of the outcome of the interaction. In this paper, we present a human-subjects study (N = 22) aimed at understanding the impact of conflicting facial and vocal emotional expressions. Specifically we explored three levels of emotional valence (unhappy, neutral, and happy) expressed in both visual (facial) and aural (vocal) forms. We also investigate three levels of head scales (down-scaled, accurate, and up-scaled) to evaluate whether head scale affects user interpretation of the conveyed emotion. We find significant effects of different multimodal expressions on happiness and trust perception, while no significant effect was observed for head scales. Evidence from our results suggest that facial expressions have a stronger impact than vocal expressions. Additionally, as the difference between the two expressions increase, the less predictable the multimodal expression becomes. For example, for the happy-looking and happy-sounding multimodal expression, we expect and see high happiness rating and high trust, however if one of the two expressions change, this mismatch makes the expression less predictable. We discuss the relationships, implications, and guidelines for social applications that aim to le
To the aim of constructing effective human-AI teams, that can be useful for improving caregiving in medicine and enhancing human performance also in other sectors (i.e., teaching), agents which interact with humans sh...
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To the aim of constructing effective human-AI teams, that can be useful for improving caregiving in medicine and enhancing human performance also in other sectors (i.e., teaching), agents which interact with humans should be endowed with an emotion recognition and management module, capable of empathy, and of modeling aspects of the Theory of Mind, in the sense of being able to reconstruct what someone is thinking or feeling. In this paper, we propose an architecture for such a module, based upon an enhanced notion of Behavior Trees. We illustrate the effectiveness of the proposed architecture on a significant example and on a wider case study.
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