Sensors 2014, 14(2), 2756-2775; doi:10.3390/s140202756

A Depth-Based Fall Detection System Using a Kinect® Sensor

* email, email, email and email
Received: 10 January 2014; in revised form: 30 January 2014 / Accepted: 8 February 2014 / Published: 11 February 2014
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: We propose an automatic, privacy-preserving, fall detection method for indoor environments, based on the usage of the Microsoft Kinect® depth sensor, in an “on-ceiling” configuration, and on the analysis of depth frames. All the elements captured in the depth scene are recognized by means of an Ad-Hoc segmentation algorithm, which analyzes the raw depth data directly provided by the sensor. The system extracts the elements, and implements a solution to classify all the blobs in the scene. Anthropometric relationships and features are exploited to recognize one or more human subjects among the blobs. Once a person is detected, he is followed by a tracking algorithm between different frames. The use of a reference depth frame, containing the set-up of the scene, allows one to extract a human subject, even when he/she is interacting with other objects, such as chairs or desks. In addition, the problem of blob fusion is taken into account and efficiently solved through an inter-frame processing algorithm. A fall is detected if the depth blob associated to a person is near to the floor. Experimental tests show the effectiveness of the proposed solution, even in complex scenarios.
Keywords: depth frame; elderly care; fall detection; human recognition; Kinect
PDF Full-text Download PDF Full-Text [819 KB, uploaded 21 June 2014 12:07 CEST]

Export to BibTeX |

MDPI and ACS Style

Gasparrini, S.; Cippitelli, E.; Spinsante, S.; Gambi, E. A Depth-Based Fall Detection System Using a Kinect® Sensor. Sensors 2014, 14, 2756-2775.

AMA Style

Gasparrini S, Cippitelli E, Spinsante S, Gambi E. A Depth-Based Fall Detection System Using a Kinect® Sensor. Sensors. 2014; 14(2):2756-2775.

Chicago/Turabian Style

Gasparrini, Samuele; Cippitelli, Enea; Spinsante, Susanna; Gambi, Ennio. 2014. "A Depth-Based Fall Detection System Using a Kinect® Sensor." Sensors 14, no. 2: 2756-2775.

Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert