Recognition of Human Behaviour using Stereo Vision and Data Gloves

This paper presents a novel method of constructing a human behaviour model by attention point (AP) analysis. The AP analysis consists of nuo steps. At the first qtep, it broadly observes human behaviour, constructs rough human behaviour model and finds APs which require detailed analysis. Then at the second step, by applying time-consuming analysis on APs in the same human behaviour, it can enhance the human behaviour model.This human behaviour model is highly abstracted and is able to change the degree of abstraction adapting to the environment so as to be applicable in a dffirent environment. We describe this method and its implementation using data gloves and a stereo vision system.We also show an experimental result inwhich a real robot observed and performed the same human behaviour successfully in a dffirent environment using this model.

[1]  Masayuki Inaba,et al.  Learning by watching: extracting reusable task knowledge from visual observation of human performance , 1994, IEEE Trans. Robotics Autom..

[2]  Kate Knill,et al.  Speaker dependent keyword spotting for accessing stored speech , 1994 .

[3]  Katsushi Ikeuchi,et al.  Toward an assembly plan from observation. I. Task recognition with polyhedral objects , 1994, IEEE Trans. Robotics Autom..

[4]  Katsushi Ikeuchi,et al.  Task-model based human robot cooperation using vision , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[5]  Alex Pentland,et al.  Real-time American Sign Language recognition from video using hidden Markov models , 1995 .

[6]  Katsushi Ikeuchi,et al.  Sensor Modeling, Probabilistic Hypothesis Generation, and Robust Localization for Object Recognition , 1995, IEEE Trans. Pattern Anal. Mach. Intell..