This invention provides a method to interpret and recognize huma faces. The 2nd-order eigenfeatures are used for lighting-invariant face description and both the 1st-order and 2nd-order eigenfeatures are used for view-angle-invariant face description. After normalization and quantization, these features can describe face effectively and efficiently. In order to further reduce the size of face descriptor, variable length code can be used to encode the quantized eigenfeatures. This invention can be used in internet multimedia database retrieval, digital library, video editing, surveillance and tracking, and other applications using face recognition and verification.
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机译：本发明提供了一种解释和识别人脸的方法。 2 nd 阶特征特征用于光照不变的面部描述，同时使用1 st 阶和2 nd 阶特征特征用于视角不变的人脸描述。经过归一化和量化后，这些功能可以有效地描述人脸。为了进一步减小面部描述符的大小，可以使用可变长度代码来对量化的特征进行编码。本发明可以用于互联网多媒体数据库检索，数字图书馆，视频编辑，监视和跟踪以及其他使用面部识别和验证的应用。
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