User Specific Data Visualization in Collaborative Virtual Environments
|Department of Computer Science|
|Virginia Tech||WWW: http://fbox.vt.edu/G/gracanin|
|Northern Virginia Center||Email: firstname.lastname@example.org|
|7054 Haycock Road, Room 310||Phone: (703) 538-8378|
|Falls Church, VA 22043, USA||Fax: (703) 538-8348|
Desktop virtual environments usually lack immersiveness due to limited input / output capabilities.
However, by taking human factors into consideration, desktop virtual environments may be just as effective in presenting a virtual world. Collaborative virtual environments (CVEs) such as collaborative design applications are very popular desktop applications, where the issues of subjective view and network performance become important. The structure and complexity of data (often from distributed and heterogeneous sources) present a challenge for effective visualization. In a collaborative environment, the user may want to see only a part of the environment and related data that is of interest. Obscuring or drafting unrelated objects in the user's local view may improve user interface by making it easier for a user to concentrate on the assigned task.
The subjectivity provides ability to add viewer dependent features. One way to achieve subjective view is manual configuration. This is relatively simple to implement, but has certain limitations. The user's interest in an object and related data is determined not only by the object itself, but also by many other factors including the object's internal and external properties, design and spatial information. Therefore, in a dynamic scene where objects may be loaded/removed at will, moved or have properties changed that might affect subjective interest, users may have to constantly re-configure their subjective views. Subjective interest for objects and related data can also be assessed by capturing human perception and behavior, and applying machine-learning algorithms to get accurate and adaptive mapping between subjective interest and the object related information. This process can be done in real-time and in the background to provide an intelligent user interface enhancement.
A working example of subjective views based on this algorithm is implemented in a first-person shooting game engine.