Intention Reading from a Fuzzy-Based Human Engagement Model and Behavioural Features

This paper presents a novel approach for a quantitative appraisal model to identify human intent so as to interact with a robot and determine an engagement level. To efficiently select an attention target for communication in multi-person interactions, we propose a fuzzy-based classification algorit...

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Bibliographic Details
Main Authors: Sang-Seok Yun, Mun-Taek Choi, Munsang Kim, Jae-Bok Song
Format: Article
Language:English
Published: SAGE Publishing 2012-08-01
Series:International Journal of Advanced Robotic Systems
Online Access:https://doi.org/10.5772/50648
Description
Summary:This paper presents a novel approach for a quantitative appraisal model to identify human intent so as to interact with a robot and determine an engagement level. To efficiently select an attention target for communication in multi-person interactions, we propose a fuzzy-based classification algorithm which is developed by an incremental learning procedure and which facilitates a multi-dimensional pattern analysis for ambiguous human behaviours. From acquired participants' non-verbal behaviour patterns, we extract the dominant feature data, analyse the generality of the model and verify the effectiveness for proper and prompt gaze behaviour. The proposed model works successfully in multiple people interactions.
ISSN:1729-8814