基于位置和纹理信息联合分布的统计人脸特征提取

M. Yilmaz, Hakan Erdogan, M. Unel
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引用次数: 1

摘要

本文提出了一种利用给定人脸图像的位置和纹理信息提取人脸特征的方法。系统可以从训练数据中自动学习位置和纹理信息。通过最大化面部特征的位置信息和纹理信息的联合分布,找到最佳的面部特征位置。通过对100张测试图像的测试,发现该方法具有良好的性能。对于相同的测试数据,该方法的性能优于活动外观模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical facial feature extraction using joint distribution of location and texture information
A facial feature extraction method is proposed in this work, which uses location and texture information given a face image. Location and texture information can automatically be learnt by the system, from a training data. Best facial feature locations are found by maximizing the joint distribution of location and texture information of facial features. Performance of the method was found promising after it is tested using 100 test images. Also it is observed that this new method performs better than active appearance models for the same test data.
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