Evaluating a new classification method using PCA to human activity recognition

The ability to recognize human activities from sensed information is very important for ubiquitous computing applications using smart identification technologies. This paper addresses a new discriminative supervised method combining the classical Principal Components Analysis with the correlation criterion for performing activity recognition in a smart home. We conduct several experiments, demonstrate the achievement of our method and show its promising results using real world dataset.