Title :
Multi-view face detection with FloatBoost
Author :
Zhang, ZhanQiu ; Mingjing Li ; Li, Stan Z. ; Zhang, Hongjiang
Author_Institution :
Beckman Inst., Illinois Univ., Urbana-Champaign, IL, USA
Abstract :
In this paper, a new boosting algorithm, called FloatBoost, is proposed to construct a strong face-nonface classifier. FloatBoost incorporates the idea of Floating Search into AdaBoost, and yields similar or higher classification accuracy than AdaBoost with a smaller number of weak classifiers. We also present a novel framework for fast multi-view face detection. A detector-pyramid architecture is designed to quickly discard a vast number of non-face sub-windows and hence perform multi-view face detection efficiently. This results in the first real-time multi-view face detection system which runs at 5 frames per second for 320x240 image sequence.
Keywords :
face recognition; image classification; search problems; AdaBoost; Floating Search; boosting algorithm; classifier; face detection; feature selection; image sequence; multi-view faces; Asia; Boosting; Computational efficiency; Detectors; Face detection; Feature extraction; Image sequences; Real time systems; Search methods; Statistics;
Conference_Titel :
Applications of Computer Vision, 2002. (WACV 2002). Proceedings. Sixth IEEE Workshop on
Conference_Location :
Orlando, FL, USA
Print_ISBN :
0-7695-1858-3
DOI :
10.1109/ACV.2002.1182179