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

Authors:
Yoshifumi Nishida;Koji Kitamura;Hiroshi Aizawa;Toshio Hori;Makoto Kimura;Takeo Kanade;Hiroshi Mizoguchi
Affiliations:
Digital Human Research Center, AIST, &CREST, JST, Aomi Koto Tokyo, Japan;Tokyo University of Science, Chiba, Japan;Tokyo Denki University, Tokyo, Japan;Digital Human Research Center, AIST, &CREST, JST, Aomi Koto Tokyo, Japan;Digital Human Research Center, AIST, &CREST, JST, Aomi Koto Tokyo, Japan;Carnegie Mellon University & Digital Human Research Center AIST, &CREST, JST;Tokyo University of Science
Venue:
Proceedings of the 9th international conference on Intelligent user interfaces
Year:
2004

Citing 1
Cited 1

Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography

Communications of the ACM

Detection of user mode shift in home

UCS'07 Proceedings of the 4th international conference on Ubiquitous computing systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.