A Hierarchical Approach for Indoor Action Recognition from New Infrared Sensor Preserving Anonymity

Félix Polla, Hélène Laurent, Bruno Emile

2020

Abstract

This article is made in the context of action recognition from infrared video footage for indoor installations. The sensor we use has some peculiarities that make the acquired images very different from those of the visible imagery. It is developed within the CoCAPS project in which our work takes place. In this context, we propose a hierarchical model that takes an image set as input, segments it, constructs the corresponding motion history image (MHI), extracts and selects characteristics that are then used by three classifiers for activity recognition purposes. The proposed model presents promising results, notably compared to other models extracted from deep learning literature. The dataset, designed for the CoCAPS project in collaboration with industrial partners, targets office situations. Seven action classes are concerned, namely: no action, restlessness, sitting down, standing up, turning on a seat, slow walking, fast walking.

Paper Citation

in Harvard Style

Polla F., Laurent H. and Emile B. (2020). A Hierarchical Approach for Indoor Action Recognition from New Infrared Sensor Preserving Anonymity. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 229-236. DOI: 10.5220/0008942002290236

in Bibtex Style

@conference{visapp20,
author={Félix Polla and Hélène Laurent and Bruno Emile},
title={A Hierarchical Approach for Indoor Action Recognition from New Infrared Sensor Preserving Anonymity},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={229-236},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008942002290236},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - A Hierarchical Approach for Indoor Action Recognition from New Infrared Sensor Preserving Anonymity
SN - 978-989-758-402-2
AU - Polla F.
AU - Laurent H.
AU - Emile B.
PY - 2020
SP - 229
EP - 236
DO - 10.5220/0008942002290236
PB - SciTePress