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Our research takes an action-centered approach to automatically learning and classifying functional objects. Our premise is that interpreting human motion is much easier than recognizing arbitrary objects because the human body has constraints on its motion. Moreover, humans tend to interact differently with different objects, so you should be able to identify an object by analyzing how people move when they manipulate it. We call these motions the human-object interaction signature. An interaction signature is a method to find and classify objects on the basis of how humans interact with those objects. The method addresses many key problems encountered in smart-home monitoring systems.