REAL TIME FALL DETECTION AND POSE RECOGNITION IN HOME ENVIRONMENTS

Jerry Aertssen, Maja Rudinac, Pieter P. Jonker

2011

Abstract

Falls are one of the major obstacles for independent living of elderly people that can be severally reduced introducing home monitoring systems that will raise the alarm in the case of emergency. In this paper we present an inexpensive and fast system for fall detection and dangerous actions monitoring in home environments. Our system is equipped only with a single camera placed on the ceiling and it performs room monitoring based on the motion information. After background subtraction, motion information is extracted using the method of Motion History Images and analysed to detect important actions. We propose to model actions as the shape deformations of motion history image in time. Every action is defined with the specific shape parameters taken at several moments in time. Model shapes are extracted in offline analysis and used for comparison in room monitoring. For testing, we designed a special room in which we monitored in various environmental conditions a total of four different actions that are dangerous for elderly people: “walking”, “falling”, “bending” and “collapsing”. Obtained results show that our system can detect dangerous actions in real time with high recognition rates and achieves better performance comparing to the state of the art methods that use similar techniques. Results encourage us to implement and test this system in real hospital environments.

Paper Citation

in Harvard Style

Aertssen J., Rudinac M. and P. Jonker P. (2011). REAL TIME FALL DETECTION AND POSE RECOGNITION IN HOME ENVIRONMENTS . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 409-414. DOI: 10.5220/0003326504090414

in Bibtex Style

@conference{visapp11,
author={Jerry Aertssen and Maja Rudinac and Pieter P. Jonker},
title={REAL TIME FALL DETECTION AND POSE RECOGNITION IN HOME ENVIRONMENTS },
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={409-414},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003326504090414},
isbn={978-989-8425-47-8},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - REAL TIME FALL DETECTION AND POSE RECOGNITION IN HOME ENVIRONMENTS
SN - 978-989-8425-47-8
AU - Aertssen J.
AU - Rudinac M.
AU - P. Jonker P.
PY - 2011
SP - 409
EP - 414
DO - 10.5220/0003326504090414