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An RGB-D based social behavior interpretation system for a humanoid social robot

Zaraki, Abolfazl, Giuliani, Manuel, Dehkordi, Maryam Banitalebi, Mazzei, Daniele, D'ursi, Annamaria and De Rossi, Danilo 2014. An RGB-D based social behavior interpretation system for a humanoid social robot. Presented at: ICRoM 2014 International Conference on Robotics and Mechatronics, Tehran, Iran, 15-17 October 2014. 2014 Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM). IEEE, pp. 185-190. 10.1109/ICRoM.2014.6990898

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Abstract

Humanoid 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.

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: Published
Schools: Engineering
Publisher: IEEE
ISBN: 978149967438
Last Modified: 24 Feb 2020 14:00
URI: http://orca.cf.ac.uk/id/eprint/128997

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