Real world sensorization for observing human behavior and its application to behavior-to-speech

This paper describes a method for robustly detecting and efficiently recognizing daily human behavior in the real world. The proposed method involves real-world sensorization using ultrasonic tags to robustly observe behavior, real-world virtualization to create a virtual environment by modeling real objects using a stereovision system, and virtual sensorization of virtualized objects in order to quickly register the handling of objects in the real world and efficiently recognizing specific human behavior. A behavior-to-speech system created based on this recognition method is also presented as a new application of this technology.