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An Improved Active Shape Model Application on Facial Feature Localization

机译:改进的主动形状​​模型在面部特征定位中的应用

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An improved active shape model is proposed in this paper. The proposed algorithm includes the following four aspects. Firstly, this paper adopts a semi-automatic facial feature points marking tool. Secondly, this paper proposes to extract 2D gradient feature on the highest level and the higher level of multi-resolution pyramid images, and use Gabor wavelet transformation to extract the lowest level’s 2D texture feature. Thirdly, this paper adopts a new method of decomposition of multi-resolution pyramid. Pyramid images are got by wavelet transformation. Finally, this paper uses an improved searching scheme of multiresolution pyramid. The length of 2D profile searching rectangle is changed according to different pyramid levels. Experimental results demonstrate that the proposed algorithm exhibits better performance than the original ASM.
机译:提出了一种改进的主动形状​​模型。所提出的算法包括以下四个方面。首先,本文采用了一种半自动的人脸特征点标记工具。其次,本文提出在最高级别和更高级别的多分辨率金字塔图像上提取2D梯度特征,并使用Gabor小波变换提取最低级别的2D纹理特征。第三,本文采用了一种新的多分辨率金字塔分解方法。金字塔图像通过小波变换获得。最后,本文使用改进的多分辨率金字塔搜索方案。二维轮廓搜索矩形的长度根据不同的金字塔等级而变化。实验结果表明,该算法具有比原始ASM更好的性能。

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