Fusion of Color and Depth Camera Data for Robust Fall Detection

Wouter Josemans, Gwenn Englebienne, Ben Kröse

Abstract

The availability of cheap imaging sensors makes it possible to increase the robustness of vision-based alarm systems. This paper explores the benefit of data fusion in the application of fall detection. Falls are a common source of injury for elderly people and automatic fall detection is, therefore, an important development in automated home care. We first evaluate a skeleton-based classification method that uses the Microsoft Kinect as a sensor. Next, we evaluate an overhead camera-based method that looks at bounding ellipse features. Then, we fuse the data from these two methods by validating the skeleton tracked by the Kinect. Data fusion proves beneficial, since the data fusion approach outperforms the other methods.

References

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Paper Citation


in Harvard Style

Josemans W., Englebienne G. and Kröse B. (2013). Fusion of Color and Depth Camera Data for Robust Fall Detection . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-47-1, pages 608-613. DOI: 10.5220/0004213406080613


in Bibtex Style

@conference{visapp13,
author={Wouter Josemans and Gwenn Englebienne and Ben Kröse},
title={Fusion of Color and Depth Camera Data for Robust Fall Detection},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={608-613},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004213406080613},
isbn={978-989-8565-47-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2013)
TI - Fusion of Color and Depth Camera Data for Robust Fall Detection
SN - 978-989-8565-47-1
AU - Josemans W.
AU - Englebienne G.
AU - Kröse B.
PY - 2013
SP - 608
EP - 613
DO - 10.5220/0004213406080613