Human Behaviour Recognition Using Appearance-Based Models

Abstract

We describe a statistical method to detect human behavior using appearance-based model of target objects. Most conventional gesture recognition systems utilize simpler method for the detection process such as background subtractions with assuming static observation conditions and those methods are not robust against camera motions, illumination changes and so on. In this paper, we propose a method to describe and recognize the appearances of target objects based on geometrical structures. Using the detection results, our system updates target tracking models. Human behavior is recognized by using the tracking models. Experimental results on human tracking and gesture recognition show the effectiveness of our method.