The impact of owner age on companionship with virtual pets

This paper focuses on issues of interaction with a particular type of mobile information system – virtual pets. It examines the impact of owner age on companionship with virtual pets, and tests the hypothesis that younger virtual pet owners will experience closer companionship with their virtual pet than older owners. This is in response to the marketing stance adopted by virtual pet manufacturers who clearly target younger people as the main consumers of their products. The hypothesis was tested using survey data and companionship was measured using the Comfort from Companion Animals Scale. Support was found for the hypothesis at all definitions of young: there is a highly significant difference between the companionship offered by a virtual pet to young people than that offered to older people. Although this finding generally indicates that virtual pets offer more, in terms of emotional-engagement, to younger people than older people we suggest that much more research in this area is needed in order to better understand the phenomenal commercial success of virtual pets. In addition, there is an abundance of literature examining the benefits of owning real pets. It is possible that a virtual pet might be able to deliver some of these, and given our result, it is likely that virtual pets will be more likely to bring these benefits to young people rather than to old peopl

VR Haptics at Home: Repurposing Everyday Objects and Environment for Casual and On-Demand VR Haptic Experiences

This paper introduces VR Haptics at Home, a method of repurposing everyday objects in the home to provide casual and on-demand haptic experiences. Current VR haptic devices are often expensive, complex, and unreliable, which limits the opportunities for rich haptic experiences outside research labs. In contrast, we envision that, by repurposing everyday objects as passive haptics props, we can create engaging VR experiences for casual uses with minimal cost and setup. To explore and evaluate this idea, we conducted an in-the-wild study with eight participants, in which they used our proof-of-concept system to turn their surrounding objects such as chairs, tables, and pillows at their own homes into haptic props. The study results show that our method can be adapted to different homes and environments, enabling more engaging VR experiences without the need for complex setup process. Based on our findings, we propose a possible design space to showcase the potential for future investigation.Comment: CHI 2023 Late-Breaking Wor

Spartan Daily, November 18, 2014

Volume 143, Issue 33https://scholarworks.sjsu.edu/spartandaily/1532/thumbnail.jp

Multimodal Hierarchical Dirichlet Process-based Active Perception

In this paper, we propose an active perception method for recognizing object categories based on the multimodal hierarchical Dirichlet process (MHDP). The MHDP enables a robot to form object categories using multimodal information, e.g., visual, auditory, and haptic information, which can be observed by performing actions on an object. However, performing many actions on a target object requires a long time. In a real-time scenario, i.e., when the time is limited, the robot has to determine the set of actions that is most effective for recognizing a target object. We propose an MHDP-based active perception method that uses the information gain (IG) maximization criterion and lazy greedy algorithm. We show that the IG maximization criterion is optimal in the sense that the criterion is equivalent to a minimization of the expected Kullback--Leibler divergence between a final recognition state and the recognition state after the next set of actions. However, a straightforward calculation of IG is practically impossible. Therefore, we derive an efficient Monte Carlo approximation method for IG by making use of a property of the MHDP. We also show that the IG has submodular and non-decreasing properties as a set function because of the structure of the graphical model of the MHDP. Therefore, the IG maximization problem is reduced to a submodular maximization problem. This means that greedy and lazy greedy algorithms are effective and have a theoretical justification for their performance. We conducted an experiment using an upper-torso humanoid robot and a second one using synthetic data. The experimental results show that the method enables the robot to select a set of actions that allow it to recognize target objects quickly and accurately. The results support our theoretical outcomes.Comment: submitte

Exploring the Design Space of Immersive Urban Analytics

Recent years have witnessed the rapid development and wide adoption of immersive head-mounted devices, such as HTC VIVE, Oculus Rift, and Microsoft HoloLens. These immersive devices have the potential to significantly extend the methodology of urban visual analytics by providing critical 3D context information and creating a sense of presence. In this paper, we propose an theoretical model to characterize the visualizations in immersive urban analytics. Further more, based on our comprehensive and concise model, we contribute a typology of combination methods of 2D and 3D visualizations that distinguish between linked views, embedded views, and mixed views. We also propose a supporting guideline to assist users in selecting a proper view under certain circumstances by considering visual geometry and spatial distribution of the 2D and 3D visualizations. Finally, based on existing works, possible future research opportunities are explored and discussed.Comment: 23 pages,11 figure

Context-Aware Mobile Augmented Reality Visualization in Construction Engineering Education

Recent studies suggest that the number of students pursuing science, technology, engineering, and mathematics (STEM) degrees has been generally decreasing. An extensive body of research cites the lack of motivation and engagement in the learning process as a major underlying reason of this decline. It has been discussed that if properly implemented, instructional technology can enhance student engagement and the quality of learning. Therefore, the main goal of this research is to implement and assess effectiveness of augmented reality (AR)-based pedagogical tools on student learning. For this purpose, two sets of experiments were designed and implemented in two different construction and civil engineering undergraduate level courses at the University of Central Florida (UCF). The first experiment was designed to systematically assess the effectiveness of a context-aware mobile AR tool (CAM-ART) in real classroom-scale environment. This tool was used to enhance traditional lecture-based instruction and information delivery by augmenting the contents of an ordinary textbook using computer-generated three-dimensional (3D) objects and other virtual multimedia (e.g. sound, video, graphs). The experiment conducted on two separate control and test groups and pre- and post- performance data as well as student perception of using CAM-ART was collected through several feedback questionnaires. In the second experiment, a building design and assembly task competition was designed and conducted using a mobile AR platform. The pedagogical value of mobile AR-based instruction and information delivery to student learning in a large-scale classroom setting was also assessed and investigated. Similar to the first experiment, students in this experiment were divided into two control and test groups. Students\u27 performance data as well as their feedback, suggestions, and workload were systematically collected and analyzed. Data analysis showed that the mobile AR framework had a measurable and positive impact on students\u27 learning. In particular, it was found that students in the test group (who used the AR tool) performed slightly better with respect to certain measures and spent more time on collaboration, communication, and exchanging ideas in both experiments. Overall, students ranked the effectiveness of the AR tool very high and stated that it has a good potential to reform traditional teaching methods