An exploration of gesture-based interaction.
Published: 2004
Language: eng
Number of pages: 103
Description: This thesis presents two related research projects exploring gesture-based interaction. The VisionWand system explores a passive wand tracked in 3D using computer vision techniques as a new input mechanism for interacting with large displays. A variety of gesture-based interaction techniques is designed to exploit the affordances of the wand, resulting in an effective alternative interface for large display interaction. Inspired by the observations made in the VisionWand and similar gesture-based interaction systems that different users have different habits in making gestures and performing tasks, we developed the adaptive gesture interface as a framework that exploits machine learning techniques to capture and utilize the users' habits on line. This framework improved the system's performance of gesture recognition, and alleviated the user's need for practice. We present a rigorous user experiment to demonstrate this improvement.
Notes: Advisers:  Allan Jepson; Ravin Balakrishnan.

Thesis (M.Sc.)--University of Toronto, 2004.

Electronic version licensed for access by U. of T. users.

Source: Masters Abstracts International, Volume: 42-06, page: 2226.

MICR copy on microfiche (2 microfiches).