Analyzing Human's Motion Pattern Using Sensor Fusion in Complex Spatial Environments

Abstract

We propose hybrid-sensing system for human tracking. This system uses laser scanners and image sensors and is applicable to wide and crowded area such as hallway of university. Concretely, human tracking using laser scanners is at base and image sensors are used for human identification when laser scanners lose persons by occlusion, entering room or going up stairs. We developed the method of human identification for this system. Our method is following: 1. Best-shot images (human images which show human feature clearly) are obtained by the help of human position and direction data obtained by laser scanners. 2. Human identification is conducted by calculating the correlation between the color histograms of best-shot images. It becomes possible to conduct human identification even in crowded scenes by estimating best-shot images. In the experiment in the station, some effectiveness of this method became clear.