Learning Latent Activities from Social Signals with Hierarchical Dirichlet Processes
Dinh Phung, Thuong Nguyen, Sunil Gupta and Svetha Venkatesh, Deakin University, Waurn Ponds, VIC, Australia
Understanding human activities is an important research topic, most noticeably in assisted-living and healthcare monitoring environments. Beyond simple forms of activity (e.g., an RFID event of entering a building), learning latent activities that are more semantically interpretable, such as sitting at a desk, meeting with people, or gathering with friends, remains a challenging problem. Supervised learning has been the typical modeling choice in the past. However, this requires labeled training data, is unable to predict never-seen-before ...