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EnglishHumanoid social robots that interact with people need to be capable of interpreting the social behavior of their interaction partners in order to respond in a socially appropriate way. In this paper, we present a social behavior interpretation system that enables a humanoid robot to recognize human social behavior by analyzing communicative signals. The system receives the constructed RGB-D scene from a Kinect sensor, extracts information about body gesture and head pose from the scene using Microsoft Kinect SDK, and recognizes eight human social behaviors using a Hidden Markov Model (HMM). We trained the eight-state HMM with a corpus of 35 recorded human-human interaction scenes. The evaluation of the system shows a weighted average recognition rate of 81% for all states. © 2014 IEEE.
| Titolo: | An RGB-D Based Social Behavior Interpretation System for a Humanoid Social Robot |
| Autori interni: | |
| Anno del prodotto: | 2014 |
| Handle: | http://hdl.handle.net/11568/602068 |
| ISBN: | 978-147996743-8 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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