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Example Based Learning for View-Based Human Face Detection

We present an example-based learning approach for locating vertical frontal views of human faces in complex scenes. The technique models the distribution of human face patterns by means of a few view-based "face'' and "non-face'' prototype clusters. At each image location, the local pattern is matched against the distribution-based model, and a trained classifier determines, based on the local difference measurements, whether or not a human face exists at the current image location. We provide an analysis that helps identify the critical components of our system.

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/7193
Date24 January 1995
CreatorsSung, Kah Kay, Poggio, Tomaso
Source SetsM.I.T. Theses and Dissertation
Languageen_US
Detected LanguageEnglish
Format21 p., 2933946 bytes, 846344 bytes, application/postscript, application/pdf
RelationAIM-1521, CBCL-112

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