SMARTCLASSYSURV - a smart camera network for distributed tracking and activity recognition and its application to assisted living

Abstract

Western societies are aging rapidly. According to [1] the US population over age 85 will triple from 4.5 million in 2003 to 14.2 million by 2040. Automated 24/7 surveillance to ensure safety of the elderly while respecting privacy becomes a major challenge. As a first step, we present a fully distributed system and architecture based on a network of smart cameras to perform geo-referenced tracking and activity recognition. Additionally an intuitive visualization is presented, where all information is integrated in one world model that is available ubiquitously. At a real world installation in an assisted living home, we demonstrate first results regarding falling person detection as one major activity for assisted living systems.