RECOGNIZING BEHAVIOR IN HAND-EYE COORDINATION PATTERNS.
RECOGNIZING BEHAVIOR IN HAND-EYE COORDINATION PATTERNS.
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识别手眼协调模式的行为。
DOI：
10.1142/s0219843609001863
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Ballard,Dana
中科院分区：
文献类型：
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作者：
Yi,Weilie;Ballard,Dana
对人类行为进行建模对于机器人的设计以及使用类人化身的人机界面来说都很重要。已经建立了建设性的模型，但它们还没有捕捉到人类行为的所有详细结构，例如在复杂任务中使用的手、头和眼睛凝视的时刻部署和协调。我们展示了如何使用来自执行任务的人类受试者的这些数据来编程动态贝叶斯网络(DBN)，该动态贝叶斯网络又可以用于识别新的性能实例。作为一个具体的演示，我们展示了复杂活动(如三明治制作)中的步骤可以被DBN实时识别。
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.