Unusual activity recognition in noisy environments

Abstract

In this paper we present a method for unusual activity recognition that is used in home environment monitoring. Monitoring systems are needed in elderly persons homes to generate automatic alarms in case of emergency. The unusual activity recognition method presented here is based on a body part segmentation algorithm that gives an estimation of how similar the current pose is compared to the poses in the training data. As there are arbitrary number of possible unusual activities it is impossible to train a system to recognize every unusual activity. We train our system to recognize a set of normal poses and consider everything else unusual. Normal activities in our case are walking and sitting down. © 2009 Springer Berlin Heidelberg.