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Angular-partitioned spin image descriptor for robust 3D facial landmark detection

机译:角度分割旋转图像描述符,用于鲁棒的3D面部界标检测

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摘要

Spin images have been widely used for representing local threedimensional (3D) shapes in 3D object recognition and 3D facial landmark detection. An improved spin image descriptor is proposed which enhances shape discrimination performance significantly over the spin image. By generating several sub-spin images for angular-partitioned subspaces, the description of unique angular features within local surfaces can be offered. The experimental results show that the proposed angular-partitioned spin image enhances the localisation accuracy of facial landmarks by 47% and detection reliability by 33% as compared to the spin image.
机译:自旋图像已被广泛用于表示3D对象识别和3D面部界标检测中的局部三维(3D)形状。提出了一种改进的自旋图像描述符,其与自旋图像相比显着增强了形状辨别性能。通过为角度划分的子空间生成几个子自旋图像,可以提供局部表面内唯一的角度特征的描述。实验结果表明,与自旋图像相比,所提出的角度分割自旋图像将面部地标的定位精度提高了47%,检测可靠性提高了33%。

著录项

  • 来源
    《Electronics Letters》 |2013年第23期|1454-1455|共2页
  • 作者

    Choi K.-S.; Kim D.-H.;

  • 作者单位

    School of Electrical, Electronics, and Communication Engineering, Korea University of Technology and Education, 1600 Chungjeol-ro, Cheonan, Chungnam 330-708, Republic of Korea|c|;

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  • 正文语种 eng
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