An Augmented Virtual Environment (AVE) fuses dynamic imagery with 3D models. An AVE provides a unique approach to visualizing spatial relationships and temporal events that occur in real-world environments. A geometric scene model provides a 3D substrate for the visualization of multiple image sequences gathered by fixed or moving image sensors. The resulting visualization is that of a world-in-miniature that depicts the corresponding real-world scene and dynamic activities. This paper describes the core elements of an AVE system, including static and dynamic model construction, sensor tracking, and image projection for 3D visualization.

In augmented reality (AR), a user can see a virtual world as well as the real world. To avoid registration problems between the virtual world and the real world, the user's viewing pose in both worlds should be kept the same. Fiducial-tracking AR is an attractive approach to the registration problem. However, most of the developed fiducialtracking AR systems have restricted workspaces. To provide a wide range of workspaces (from a small-scale desktop space to a large-scale space) and a wide range of views (from far views to detailed views), an AR system should have scalability. In this paper, we present multiring color fiducial systems and a real-time fiducial detection method for scalable fiducial-tracking AR. We analyze the optimal ring width and develop formulas to obtain the optimal fiducial set with applicationspecific inputs. We develop a real-time ring-detection method that converts the five-DOF ellipse-detection problem to a series of simple steps with a 1-D segmentfilter and multithreshold segmentation. The results lead to a simple and inexpensive means of achieving scalable-area tracking for AR and an approach that is suitable as an optical tracking method for VR as well.

Virtual reality (VR) technology offers new options for the creation of sophisticated tools that could be applied in the areas of assessment and rehabilitation of cognitive and functional processes. VR systems allow for the precise presentation and control of dynamic, multisensory, three-dimensional (3-D) stimulus environments, as well as the recording of all behavioral responses that occur within them. Assessment and rehabilitation scenarios that would be difficult if not impossible to deliver using conventional neuropsychological methods are now being developed that take advantage of these VR assets. If empirical studies demonstrate effectiveness, virtual environments (VEs) could be of considerable value for better understanding, measuring, and treating persons with impairments due to traumatic brain injury, neurological disorders, and learning disabilities. This article describes the progress of a VR research program at the USC Integrated Media Systems Center and Information Sciences Institute that has developed and investigated the use of a series of VEs designed to target (i) molecular visuospatial skills using a 3-D, projection-based ImmersaDesk system, and (ii) attention (and soon memory and executive functioning) processes within ecologically valid functional scenarios utilizing a head-mounted display (HMD). Results from completed research, rationales and methodology of works in progress, and our plan for future work is presented. Our primary vision has been to develop VR systems that target cognitive processes and functional skills that are of relevance to a wide range of patient populations with central nervous system (CNS) dysfunction, as well as for the assessment of unimpaired performance. We have also sought to select cognitive/functional targets that intuitively appear well matched to the specific assets available with currently available VR technology.