An Address-Event Fall Detector for Assisted Living Applications

Abstract

In this paper, we describe an address-event vision system designed to detect accidental falls in elderly home care applications. The system raises an alarm when a fall hazard is detected. We use an asynchronous temporal contrast vision sensor which features sub-millisecond temporal resolution. The sensor reports a fall at ten times higher temporal resolution than a frame-based camera and shows 84% higher bandwidth efficiency as it transmits fall events. A lightweight algorithm computes an instantaneous motion vector and reports fall events. We are able to distinguish fall events from normal human behavior, such as walking, crouching down, and sitting down. Our system is robust to the monitored person's spatial position in a room and presence of pets.