Upper Body Detection and Feature Set Evaluation for Body Pose Classification

Laurent Fitte-Duval, Alhayat Ali Mekonnen, Frédéric Lerasle

Abstract

This work investigates some visual functionalities required in Human-Robot Interaction (HRI) to evaluate the intention of a person to interact with another agent (robot or human). Analyzing the upper part of the human body which includes the head and the shoulders, we obtain essential cues on the person’s intention. We propose a fast and efficient upper body detector and an approach to estimate the upper body pose in 2D images. The upper body detector derived from a state-of-the-art pedestrian detector identifies people using Aggregated Channel Features (ACF) and fast feature pyramid whereas the upper body pose classifier uses a sparse representation technique to recognize their shoulder orientation. The proposed detector exhibits state-of-the-art result on a public dataset in terms of both detection performance and frame rate. We also present an evaluation of different feature set combinations for pose classification using upper body images and report promising results despite the associated challenges.

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Paper Citation


in Harvard Style

Fitte-Duval L., Mekonnen A. and Lerasle F. (2015). Upper Body Detection and Feature Set Evaluation for Body Pose Classification . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-090-1, pages 439-446. DOI: 10.5220/0005313104390446


in Bibtex Style

@conference{visapp15,
author={Laurent Fitte-Duval and Alhayat Ali Mekonnen and Frédéric Lerasle},
title={Upper Body Detection and Feature Set Evaluation for Body Pose Classification},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={439-446},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005313104390446},
isbn={978-989-758-090-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2015)
TI - Upper Body Detection and Feature Set Evaluation for Body Pose Classification
SN - 978-989-758-090-1
AU - Fitte-Duval L.
AU - Mekonnen A.
AU - Lerasle F.
PY - 2015
SP - 439
EP - 446
DO - 10.5220/0005313104390446