识别手眼协调模式中的行为。
RECOGNIZING BEHAVIOR IN HAND-EYE COORDINATION PATTERNS.
作者信息
Yi Weilie, Ballard Dana
机构信息
Microsoft Corporation One Microsoft Way, Redmond, WA 98052, USA,
出版信息
Int J HR. 2009;6(3):337-359. doi: 10.1142/S0219843609001863.
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.
对人类行为进行建模，对于机器人设计以及使用类人化身的人机界面而言都很重要。虽然已经构建了一些建设性模型，但它们尚未捕捉到人类行为的所有详细结构，比如在复杂任务中手、头部和目光的瞬间部署与协调。我们展示了如何利用人类执行任务时产生的数据来对动态贝叶斯网络（DBN）进行编程，而该网络又可用于识别新的行为表现实例。作为一个具体的示例，我们表明，像制作三明治这样的复杂活动中的步骤，DBN能够实时识别。
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