Recognizing household activities from human motion data using active learning and feature selection

Liyue Zhao, Xi Wang, Gita Sukthankar, Asim Smailagic
2010 Technology and Disability  
The ability to accurately recognize human household activities is an important stepping stone toward creating home living assistance systems in the future. Classifying these activities can be difficult due to noisy sensor data, lack of labeled training samples for rare actions and large individual differences in activity execution. In this article, we present two techniques for improving the supervised classification of human activities from motion data: 1) an active learning framework to
more » ... e sample efficiency and 2) intelligent feature selection to reduce training time. We demonstrate our techniques using the CMU Multimodal Activity database.
doi:10.3233/tad-2010-0284 fatcat:wmrx3r4hujdepdnfctnyzhveue