In this paper, a robust real-time face detection system based on the integration of different location methods is proposed. A hierarchical architecture composed of three levels has been designed. At the first level, a change detection method is applied to detect blobs of moving objects (i.e., humans) in the scene. Then, the silhouette of each blob is analyzed to focalize the attention of the system on small image areas where the probability of finding human heads is high. At the second level, two different methods, i.e., the skin color and the principal component analysis, are applied to locate human faces. Finally, the higher level fuses the obtained location data to improve the face detection reliability. The system has been tested in outdoor environments in the context of a video-based surveillance system.
A Robust Face Detection System For Real Environments
FORESTI, Gian Luca;MICHELONI, Christian;SNIDARO, Lauro
2003-01-01
Abstract
In this paper, a robust real-time face detection system based on the integration of different location methods is proposed. A hierarchical architecture composed of three levels has been designed. At the first level, a change detection method is applied to detect blobs of moving objects (i.e., humans) in the scene. Then, the silhouette of each blob is analyzed to focalize the attention of the system on small image areas where the probability of finding human heads is high. At the second level, two different methods, i.e., the skin color and the principal component analysis, are applied to locate human faces. Finally, the higher level fuses the obtained location data to improve the face detection reliability. The system has been tested in outdoor environments in the context of a video-based surveillance system.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
