Action Recognition Through an Action Generation Mechanism

摘要

In this paper, we studied how actions of others can be recognized by the very same mechanisms that generate similar actions. We used action generation mechanisms to simulate actions and compare resulting trajectories with the observed one as the action unfolds. Specifically, we modified Dynamic Movement Primitives (DMP) for online action recognition and used them as our action generation mechanism. A human demonstrator applied three di⇥erent actions on two di⇥erent objects. Recordings of these actions were used to train DMPs and test our approach. We showed that our system is capable of online action recognition within approximately the first one-third of the observed action with a success rate of over %90. Online capabilities of the recognition system were also tested in an interactive game with the robot.