Real world activity summary for senior home monitoring

From a senior person's daily activities, one can tell a lot about the health condition of the senior person. Thus we believe that senior home activity analysis will play an important role in the health care of senior people. Toward this goal, we propose a senior home activity summary system. One challenging problem in such a real world application is that senior's activities are usually accompanied by nurse's walking. It is impractical to predefine and label all the potential activities of all the potential visitors. To address this problem, we propose a novel feature filtering technique to reduce or eliminate the effects of the interest points that belong to other people. To evaluate the proposed activity summary system, we have collected a senior home activity dataset (SAR), and performed activity recognition for eating and walking classes. The experimental results show that the proposed system provides quite accurate activity summaries for a real world application scenario.