Key point localization for 3d model generation from facial illustrations using SURF and color features

R. Aoki, Shun Aoki, Yakumo Ohtagaki, R. Miyamoto
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引用次数: 2

Abstract

This paper proposes a novel scheme to improve localization accuracy of facial key points in facial illustrations. The proposed scheme estimates the location of facial key points considering global structure of facial key points evaluated by RANSAC like scheme where local evaluation is performed with SURF and color features. Experimental results using a data set composed of facial illustrations show that the estimation error can be reduced to about 8.93 pixels per a key point.
关键点定位从面部插图生成3d模型使用SURF和颜色特征
本文提出了一种提高人脸图中人脸关键点定位精度的新方案。该方案考虑了RANSAC类方案评估人脸关键点的全局结构,利用SURF和颜色特征进行局部评估。实验结果表明,该算法可以将人脸图像的估计误差降低到8.93像素/点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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