An unsupervised learning method for human activity recognition based on a temporal qualitative model
Abstract
In this paper, we investigate the problem of monitoring human activities using a network of sensors, including video cameras, in a smart home environment. We introduce an unsupervised method for mining a new kind of qualitative temporally structured activity models from sensor data. We present an application of our method to the recognition of activities of daily living in an elderly care context.
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