Robust nose detection in 3D facial data using local characteristics
Robust nose detection in 3D facial data using local characteristics
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DOI：
10.1109/icip.2004.1421473
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发表时间：
2004-10
期刊：
影响因子：
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通讯作者：
Chenghua Xu;Yunhong Wang;T. Tan;Long Quan
中科院分区：
文献类型：
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作者：
Chenghua Xu;Yunhong Wang;T. Tan;Long Quan
特征点的检测问题出现在许多科学和工程领域。本文针对三维人脸深度数据，提出了一种稳健的方法来解决一个具体问题，即利用局部统计特征和夹角曲线定位鼻唇和鼻脊。这项工作对三维人脸建模、识别和配准具有重要意义。该方法的主要特点是全自动处理，能够处理噪声和不完整的输入数据，不受旋转和平移的影响，对不同的分辨率具有很强的适应性。在不同数据库上的实验结果充分说明了该方法的健壮性和可行性。
The problem of detecting the feature points arises in many fields of science and engineering. In this paper, we focus on the 3D face range data and propose a robust scheme to solve a specific problem, i.e. locating the nose lip and nose ridge using the local statistic features and included angle curve. This work is very significant to 3D face modelling, recognition and registration. The key features of our method are the fully automated processing, the ability to deal with noisy and incomplete input data, the immunity to the rotation and translation and the adaptability to the different resolution. The experimental results in different databases fully show the robust and feasibility of the proposed method.