Improving the man-machine interface through the analysis of expressiveness in human movement

Abstract

In this paper our recent development in the research of computational models and algorithms for the real-time analysis of full-body human movement are presented. Our aim is to find methods and techniques to extract cues relevant to KANSEI and emotional content in human expressive gesture in real time. Analysis of expressiveness in human gestures can contribute to new paradigms for the design of improved human-robot interfaces. As a main concrete result of our research work, a software platform named EyesWeb has been developed and is distributed for free (www.eyesweb.org). EyesWeb supports research in multimodal interaction, and provides a concrete tool for developing real-time interactive applications. Human movement analysis is provided by means of a library of algorithms for sensors and video processing, features extraction, gesture segmentation, etc. A visual environment is provided to compose such basic algorithms in order to develop more sophisticated analysis techniques.