GWINDOWS: Towards Robust Perception-Based UI
CVPR Workshops(2003)
摘要
Perceptual user interfaces promise modes of fluid computer-human interaction that complement the mouse and keyboard, and have been especially motivated in non-desktop scenarios, such as kiosks or smart rooms. Such interfaces, however, have been slow to see use for a variety of reasons, including the computational burden they impose, a lack of robustness outside the laboratory, unreasonable calibration de- mands, and a shortage of sufficiently compelling applications. We have tackled some of these difficulties by using a fast stereo vision algorithm for recognizing hand positions and gestures. Our system uses two inexpensive video cameras to extract depth information. This depth information enhances automatic object detection and tracking robustness, and may also be used in applications. We demonstrate the algorithm in combination with speech recognition to perform several basic window management tasks, report on a user study probing the ease of using the system, and discuss the implications of such a system for future user interfaces. maintained in very limited quantities, and require laborious calibration. We believe that for these novel interfaces to be adopted, they must perform robustly outside of the laboratory, be computationally inexpensive, rely on common hardware, and be easy to set up and calibrate. Also, they cannot rely on intrusive devices such as gloves, headsets or close-talk microphones. In this paper, we propose a real-time stereo vision algorithm for perceptual user interfaces that is designed with these constraints in mind. We review an application of the algorithm in a multimodal system, named GWINDOWS, that allows users to manipulate on-screen objects with gestures and voice.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络