Volleyball, a sport characterized by unpredictable factors such as ball trajectory, teammate actions, and strategic positioning, presents a challenge when it comes to modeling and training due to its high levels of complexity. Successful gameplay relies on the coordinated efforts of all team members in the receiving, setting, and attacking phases. In real-life competitions, the setter's on-ball ability and decision-making are particularly crucial to the team's offensive success: To improve the training of setters in observing player movements while running and making informed attacking decisions, we propose the design of a virtual reality (VR) system which aims to enhance players' setting skills and strategic thinking to achieve more successful offensive plays with a lower cost.

Optical illusions have been brought into recent video games to enhance gaming experiences. However, a large corpus of optical illusions remains unused, while few games incorporate illusions seamlessly. To mitigate the gap, we propose a workflow to guide game designers in applying optical illusions to their video games, i.e., in making more illusion games. In particular, our workflow consists of 5 stages: (1) choosing a game object, (2) searching for a matching illusion, (3) selecting an illusion mechanic, (4) integrating the selected illusion into the game, and (5) optionally revealing the illusion. To facilitate our workflow, we provide a tag database with 163 illusions that are labeled by their in-game visual elements and desired effects. We also provide example editing interfaces of 6 illusions for game designers. We walk through our workflow and showcase 6 resulting illusion games. We implemented these 6 games (with and without illusion) and conducted a 12-participant study to gain a preliminary understanding of how illusions enhance gaming experiences. To evaluate our workflow, we invited 6 game designers and 6 experienced players to follow our workflow and design their own illusion games, where 3 experienced game designers completed 2-week in-depth developments. We report their games, qualitative feedback and discuss reflection on our workflow, database and editing interfaces.

We present Haptic-go-round, a surrounding platform that allows deploying props and devices to provide haptic feedbacks in any direction in virtual reality experiences. The key component of Haptic-go-round is a motorized turntable that rotates the correct haptic device to the right direction at the right time to match what users are about to touch. We implemented a working platform including plug-and-play prop cartridges and a software interface that allow experience designers to agilely add their haptic components and use the platform for their applications. We conducted technical experiments and two user studies on Haptic-go-round to evaluate its performance. We report the results and discuss our insights and limitations.

An error concealment using non-uniform rational B-spline (NURBS) is proposed. NURBS has been employed by many CAD/CAM systems as a fundamental geometry representation. Despite the fact that NURBS has gained tremendous popularity from the CAD/CAM and computer graphics community, its application on exploring the image problem only received little attention. On the other hand, the image contents might be corrupted or lost during transmission. Although there are quite a few existing techniques, yet developing an effective approach to conceal the error remains as one of the hottest research topics. Thus the aim of this study is to develop an image reconstruction technique using NURBS. The key idea is to use NURBS to represent the portion of image data without corruption. By accomplishing this, a single-hidden layer neural network is employed to learn the appropriate control points of NURBS. After learning, NURBS is then used to render the corrupted image data. Experimental results indicate that the proposed approach exhibits promising performance.