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Efficient classification of three dimensional face models for human identification and other applications

机译:对人脸识别和其他应用程序的三维人脸模型进行有效分类

摘要

Three dimensional face recognition via vectorizing samples that are in an enrollment data base. The vectors are formed by comparing faces in the enrollment database with reference faces, and determining differences between the actual faces and the reference faces. Those differences are then formed into an N dimensional vector representing the classified faces. A query face is then similarly vectorized and compared to precomputed vectors indicative of the faces in the database. Another technique is described for updating the reference faces based on an error level.
机译:通过矢量化注册数据库中的样本进行三维人脸识别。通过将注册数据库中的面孔与参考面孔进行比较,并确定实际面孔和参考面孔之间的差异,来形成矢量。然后,将这些差异形成代表分类面孔的N维向量。然后将查询人脸类似地矢量化,并与指示数据库中人脸的预先计算出的向量进行比较。描述了用于基于误差水平更新参考面的另一种技术。

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