Multi-camera egocentric activity detection for personal assistant

We demonstrate an egocentric human activity assistant systemthat has been developed to aid people in doing explicitly encoded motion behavior, such as operating a home infusion pump in sequence. This system is based on a robust multi-camera egocentric human behavior detection approach. This approach detects individual actions in interesting hot regions by spatio-temporal mid-level features, which are built by spatial bag-of-words method in time sliding window. Using a specific infusion pump as a test case, our goal is to detect individual human actions in the operations of a home medical device to see whether the patient is correctly performing the required actions.