The studies of player reviews can help game developers design and optimize VR games. To this end, we investigated 288,685 reviews from 506 VR games on the Steam platform to analyze their sentiment tendencies using the...
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ISBN:
(纸本)9781665484022
The studies of player reviews can help game developers design and optimize VR games. To this end, we investigated 288,685 reviews from 506 VR games on the Steam platform to analyze their sentiment tendencies using the machine learning-based model SKEP, which finds that although some of the reviews are "recommend", they actually have opposite emotional tendencies. We also study the syntactic properties based on the natural language processing (NLP) kits Stanza and NLTK library, and we find that cybersickness is a significant concern for players.
This work explores a new usage of Augmented Reality (AR) to extend perception and interaction within physical areas ahead of ourselves. To do so, we propose to detach ourselves from our physical position by creating a...
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ISBN:
(数字)9781665453257
ISBN:
(纸本)9781665453257
This work explores a new usage of Augmented Reality (AR) to extend perception and interaction within physical areas ahead of ourselves. To do so, we propose to detach ourselves from our physical position by creating a controllable "digital copy" of our body that can be used to navigate in local space from a third-person perspective. With such a viewpoint, we aim to improve our mental representation of distant space and understanding of action possibilities (called affordances), without requiring us to physically enter this space. Our approach relies on AR to virtually integrate the user's body in remote areas in the form of an avatar. We discuss concrete application scenarios and propose several techniques to manipulate avatars in the third person as a part of a larger conceptual framework. Finally, through a user study employing one of the proposed techniques (puppeteering), we evaluate the validity of using third-person embodiment to extend our perception of the real world to areas outside of our proximal zone. We found that this approach succeeded in enhancing the user's accuracy and confidence when estimating their action capabilities at distant locations.
With the goal of exploring the impact of transparency on selection in augmented reality (AR), we present a Fitts' law experiment with 18 participants, comparing three different input methods (finger based Pointing...
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ISBN:
(纸本)9781665484022
With the goal of exploring the impact of transparency on selection in augmented reality (AR), we present a Fitts' law experiment with 18 participants, comparing three different input methods (finger based Pointing Gesture, controller using the Touchpad, and controller using Raycast), across 4 different target transparency levels (0%, 30%, 60%, and 90%) in an optical see-through AR head-mounted display. The results indicate that transparency has little effect on selection throughput and error rates. Overall, the Raycast input method performed significantly better than the pointing gesture and Touchpad inputs in terms of error rate and throughput in all opacity conditions.
We present an exploratory study to compare the haptic, visual, and verbal modalities for communicating distance information in a shared virtual environment. The results show that the visual modality decreased the dist...
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ISBN:
(纸本)9781665484022
We present an exploratory study to compare the haptic, visual, and verbal modalities for communicating distance information in a shared virtual environment. The results show that the visual modality decreased the distance estimation error while the haptic modality decreased the completion time. The verbal modality increased the sense of copresence but was the least preferred modality. These results suggest that a combination of modalities could improve communication of distance information to a partner. These findings can contribute to improving the design of collaborative VR systems and open new research perspectives on studying the effectiveness of multimodal interaction.
Our research focuses on how physical props in virtual reality (VR) can affect users' time perception. We designed an experiment with the goal of comparing users' perception of time when using physical props in...
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ISBN:
(纸本)9781665484022
Our research focuses on how physical props in virtual reality (VR) can affect users' time perception. We designed an experiment with the goal of comparing users' perception of time when using physical props in VR as compared to standard controllers and only virtual elements. In order to quantify this effect, time estimates for both conditions are compared to time estimates for a matching real-world task. In this experiment, participants assume the role of a firefighter trainee, going through a HAZMAT scenario, where they touch and interact with different physical props that match the virtual elements of the scene.
The occlusion function benefits augmented reality (AR) in many aspects. However, existing occlusion-capable optical see-through augmented reality (OC-OST-AR) displays are designed by integrating virtual displays into ...
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ISBN:
(纸本)9781665484022
The occlusion function benefits augmented reality (AR) in many aspects. However, existing occlusion-capable optical see-through augmented reality (OC-OST-AR) displays are designed by integrating virtual displays into a dedicated occlusion-capable architecture, hereby, we miss merits from emerging OST-AR displays. In this article, we propose an external occlusion module that can be added to common OST-AR displays. Per-pixel occlusion is supported with a small form-factor by using polarization-based optical path compression. The occlusion function can be switched on/off by controlling the incident light polarization. A prototype within a volume of 6 x 6 x 3cm is built. A preliminary experiment proves that occlusion is realized successfully.
Social virtual reality is getting mainstream not only for entertainment purposes but also for productivity and education. This makes the design of social VR scenarios functional to support the operator's performan...
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ISBN:
(纸本)9781665484022
Social virtual reality is getting mainstream not only for entertainment purposes but also for productivity and education. This makes the design of social VR scenarios functional to support the operator's performance. We present a physiologically-adaptive system that optimizes for visual complexity in a dual-task scenario based on electrodermal activity. Specifically, we propose a system that adapts the amount of non-player characters while jointly performing an N-Back task (primary) and visual detection task (secondary). Our preliminary results show that when optimizing the complexity of the secondary task, users report an improved user experience.
This work investigates the use of Virtual Reality (VR) to present forensic evidence to the jury in a courtroom trial. The findings of a between-participant user study on comprehension of an expert statement are presen...
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ISBN:
(纸本)9781665496179
This work investigates the use of Virtual Reality (VR) to present forensic evidence to the jury in a courtroom trial. The findings of a between-participant user study on comprehension of an expert statement are presented, examining the benefits and issues of using VR compared to traditional courtroom presentation (being still images). Participants listened to a forensic scientist explain bloodstain spatter patterns while viewing a mock crime scene in either VR or as still images in video format. Under these conditions, we compared understanding of the expert domain, mental effort and content recall. We found that VR significantly improves the understanding of spatial information and knowledge acquisition. We also identify different patterns of user behaviour depending on the display method. We conclude with suggestions on how to best adapt evidence presentation to VR.
Using Machine Learning and Deep Learning to predict cognitive tasks from electroencephalography (EEG) signals has been a fastdeveloping area in Brain-Computer Interfaces (BCI). Yet, one fundamental challenge is that E...
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ISBN:
(纸本)9783031054570;9783031054563
Using Machine Learning and Deep Learning to predict cognitive tasks from electroencephalography (EEG) signals has been a fastdeveloping area in Brain-Computer Interfaces (BCI). Yet, one fundamental challenge is that EEG signals are vulnerable to various noises. This paper identifies two types of noise: external noise and internal noise. External noises are caused by subjects' movement or sensors' instability, and internal noises result from the subjects' random mental activities due to the subjects' mind wandering during the experiment. When the participants conduct other mental activities researchers cannot infer, it will result in data corresponding to' unknown' tasks. We pioneer a human-In-The-Loop (HITL) machine learning model, EEG4Home, to handle both types of noise and increase the accuracy of predicting known tasks. We introduce a plateau threshold to remove external noise and an unknown threshold set to detect unknown tasks to remove internal noise. Both unsupervised (such as K-Means) and supervised (Such as Random Forests, CNN, and RNN) learning algorithms are implemented in this HITL approach. We use the Thinkingl BCI experiments dataset with sixty subjects (available to academic researchers by request). The average prediction accuracy of known tasks has increased from 56.8% to 65.1%. Overall, this EEG4Home model enables researchers or end-users to gain higher prediction accuracy and more interpretable results.
Acquiring health knowledge is essential and starts already in primary school. Augmented Reality (AR) helps to convey complex topics in a more understandable way. In this paper, we present the prototype of KARLI, the &...
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ISBN:
(纸本)9781665484022
Acquiring health knowledge is essential and starts already in primary school. Augmented Reality (AR) helps to convey complex topics in a more understandable way. In this paper, we present the prototype of KARLI, the "Kid-friendly Augmented Reality Learning Interface". This AR smartphone app for in-school use is designed for age level 8 to 10, enabling pupils to explore a 3D model of the human body based on the primary school curriculum. Underlining the importance of kid-friendly app development and testing, our evaluation results of 38 pupils and 3 teachers indicate that KARLI is suitable and helpful for health education in primary schools.
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