Probabilistic method of real-time person detection using color image sequences

Proposes a probabilistic method for detecting people in a corridor using a sequence of color images. In a learning phase, the templates of people and the color properties of skins, a background without shadows, and a background with shadows of people are obtained. In a detection phase, the probabilities of the color of each pixel belonging to various objects are computed. Then templates of a person are placed at various image positions and the criterion of matching to a person is computed for each position. If a template is matched to a person, a more precise position of the person is determined near the matched position. We carry out an experiment using real image sequences to show the effectiveness of the method