A Component-based Framework for Face Detection and Identification

被引：0
作者：
Bernd Heisele
Thomas Serre
T. Poggio
机构：
[1] Honda Research Institute USA in Cambridge and the Center for Biological and Computational Learning at M.I.T. Cambridge,the Department of Brain and Cognitive Sciences and the Computer Science and Artificial Intelligence Laboratory at M.I.T.
[2] McGovern Institute for Brain Research,undefined
[3] the Center for Biological and Computational Learning,undefined
来源：
International Journal of Computer Vision | 2007年 / 74卷
关键词：
face detection; face identification; face recognition; object detection; object recognition; support vector; machines; components; fragments; parts; hierarchical classification;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We present a component-based framework for face detection and identification. The face detection and identification modules share the same hierarchical architecture. They both consist of two layers of classifiers, a layer with a set of component classifiers and a layer with a single combination classifier. The component classifiers independently detect/identify facial parts in the image. Their outputs are passed the combination classifier which performs the final detection/identification of the face.
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收藏
页码：167 / 181
页数：14
相关论文
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