基于自适应半径的3d人脸分割

Rabiu Habibu, M. Saripan, M. Marhaban, S. Mashohor
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引用次数: 4

摘要

人脸检测与分割是人脸识别、面部表情识别等人脸相关过程的重要前提步骤。一种自动分割给定人脸图像的方法,无论其大小和方向如何,不仅可以简化后续的人脸分析任务,而且可以提高其性能。本文提出了一种基于自适应半径的人脸分割方法。我们利用人脸的固有属性,从高斯和平均曲率的脸表面来分割每个脸。使用UPM-3DFE和Gavab三维人脸数据库对新方法进行了测试。视觉检测结果表明,该方法的分割准确率高达99.23%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3d-based face segmentation using adaptive radius
Face detection and segmentation is an important prerequisite step for many face related processes such as face recognition and facial expression recognition. A method that automatically segments the given faces images irrespective of their different sizes and orientations will not only ease the subsequent face analysis task but will as well enhances its performance. In this work, an adaptive radius based face segmentation method is presented. We utilised the face's intrinsic properties derived from Gaussian and mean curvature of the face surface to segment each face. The UPM-3DFE and Gavab 3D face databases were used in testing the new method. Visual inspection of the result indicated that the novel method can attained up to 99.23% segmentation accuracy.
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