Robust Human Detection and Tracking in Intelligent Environments by Information Fusion of Color and Infrared Video

This paper is related to ambient intelligence systems capable of locating and tracking humans. These are the first steps of a human-centered ambient intelligent system, ranging from data acquisition to robust tracking, for the purpose of interpreting human behaviors in monitored environments. The first objective is to improve human detection through the fusion of thermal-infrared and color video segmentation. On the level following to segmentation, the traditional tracking problems (e.g. occlusions, crossings, etc.) are faced. Finally, the use of several classifiers such as support-vector machines and artificial neural networks are proposed to enhance the tracking level. The work proposes a combination of both color and thermal infrared spectra in human tracking.