People management framework using a 2D camera for human-robot social interactions

Abstract : In order to perform tasks and offer socially acceptable human-robot interactions, domestic robots need the ability to collect various information about people. In this paper, we propose a framework that allows the extraction of high-level person features from a 2D camera in addition to tracking people over time. The proposed people management framework aggregates body and person features including an original pose estimation using only a 2D camera. At this time, people pose and posture, clothing colors, face recognition are combined with tracking and re-identification abilities. This framework has been successfully used by the LyonTech team in the RoboCup@Home 2018 competition with a Pepper robot from SoftBank Robotics where its utility for domestic robot applications was demonstrated.
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Contributor : Jacques Saraydaryan <>
Submitted on : Thursday, October 17, 2019 - 3:11:50 PM
Last modification on : Tuesday, November 19, 2019 - 1:56:10 AM


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  • HAL Id : hal-02318916, version 1



Jacques Saraydaryan, Raphael Leber, Fabrice Jumel. People management framework using a 2D camera for human-robot social interactions. 23rd Annual RoboCup International Symposium RCS, Jul 2019, Sydney, Australia. ⟨hal-02318916⟩



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