title: RECOGNIZING BEHAVIOR IN HAND-EYE COORDINATION PATTERNS.
abstract: Modeling human behavior is important for the design of robots as well as human-computer interfaces that use humanoid avatars. Constructive models have been built, but they have not captured all of the detailed structure of human behavior such as the moment-to-moment deployment and coordination of hand, head and eye gaze used in complex tasks. We show how this data from human subjects performing a task can be used to program a dynamic Bayes network (DBN) which in turn can be used to recognize new performance instances. As a specific demonstration we show that the steps in a complex activity such as sandwich making can be recognized by a DBN in real time.
authors.affiliation: Microsoft Corporation One Microsoft Way, Redmond, WA 98052, USA, weiliey@microsoft.com.
authors.forename: Weilie
authors.initials: W
authors.lastname: Yi
authors.forename: Dana
authors.initials: D
authors.lastname: Ballard