Thanks to recent advances on motion capture devices and stereoscopic consumer displays, animated virtual characters can now realistically interact with users in a variety of applications. We investigate in this paper the effect of avatars, stereo vision and display size on task execution in immersive virtual environments. We report results obtained with three experiments in varied configurations that are commonly used in rehabilitation applications. The first experiment analyzes the accuracy of reaching tasks under different system configurations: with and without an avatar, with and without stereo vision, and employing a 2D desktop monitor versus a large multi-tile visualization display. The second experiment analyzes the use of avatars and user-perspective stereo vision on the ability to perceive and subsequently reproduce motions demonstrated by an autonomous virtual character. The third experiment evaluates the overall user experience with a complete immersive user interface for motion modeling by direct demonstration. Our experiments expose and quantify the benefits of using stereo vision and avatars, and show that the use of avatars improve the quality of produced motions and the resemblance of replicated msotions; however, direct interaction in user-perspective leads to tasks executed in less time and to targets more accurately reached. These and additional tradeoffs are important for the effective design of avatar-based training systems.

We present in this paper a new GPU-based approach to compute Shortest Path Maps (SPMs) from a source point in a polygonal domain. Our method takes advantage of GPU polygon rasterization with shader programming. After encoding the SPM in the frame buffer, globally shortest paths are efficiently computed in time proportional to the number of vertices in the path, and length queries are computed in constant time. We have evaluated our method in multiple environments and our results show a significant speedup in comparison to previous approaches.

We present a new software framework for the development of immersive collaborative virtual reality applications with emphasis on full-body interaction with virtual humans. The framework is designed to be scalable and adaptable to different hardware configurations, using either commodity or more expensive hardware setups. High level programming abstractions handle object replication and communication channels for configurations based on multiple rendering nodes. The system provides tools for full-body character animation, real-time full-body tracking and retargeting to virtual humans, including motion reconstruction from a small set of sensors. Such capabilities allow new full-body interaction metaphors to be developed in fixed or user-perspective stereo visualization. The framework is scalable, customizable, cross-platform and it is only based on tools with source code available.

We present new solutions based on Virtual Reality technologies for improving the delivery of physical therapy and rehabilitation. Three main aspects are addressed: 1) the ability to allow therapists to create new exercises and therapy programs intuitively by direct demonstration, 2) automatic therapy delivery and monitoring with the use of an autonomous virtual tutor that can monitor and quantitatively assess the motions performed by the patient, and 3) networked collaborative remote therapy sessions via connected applications displaying the motions of both the therapist and the patient. We also provide 3D assessment tools for monitoring changes in the range of motion, and for allowing the visualization of a number of properties during or after the execution of exercises. The presented system has been implemented for a low-cost hardware solution based on Kinect and for a high-end immersive virtual reality facility.