کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
526450 | 869115 | 2007 | 18 صفحه PDF | دانلود رایگان |
We present a novel approach for visual tracking of structured behaviour as observed in human–computer interaction. An automatically acquired variable-length Markov model is used to represent the high-level structure and temporal ordering of gestures. Continuous estimation of hand posture is handled by combining the model with annealed particle filtering. The stochastic simulation updates and automatically switches between different model representations of hand posture that correspond to distinct gestures. The implementation executes in real time and demonstrates significant improvement in robustness over comparable methods. We provide a measurement of user performance when our method is applied to a Fitts’ law drag-and-drop task, and an analysis of the effects of latency that it introduces.
Journal: Computer Vision and Image Understanding - Volume 108, Issues 1–2, October–November 2007, Pages 98–115