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    李 英, 赖剑煌, 阮邦志. 多模板ASM方法及其在人脸特征点检测中的应用[J]. 计算机研究与发展, 2007, 44(1): 133-140.
    引用本文: 李 英, 赖剑煌, 阮邦志. 多模板ASM方法及其在人脸特征点检测中的应用[J]. 计算机研究与发展, 2007, 44(1): 133-140.
    Li Ying, Lai Jianhuang, Yuen Pongchi. Multi-Template ASM and Its Application in Facial Feature Points Detection[J]. Journal of Computer Research and Development, 2007, 44(1): 133-140.
    Citation: Li Ying, Lai Jianhuang, Yuen Pongchi. Multi-Template ASM and Its Application in Facial Feature Points Detection[J]. Journal of Computer Research and Development, 2007, 44(1): 133-140.

    多模板ASM方法及其在人脸特征点检测中的应用

    Multi-Template ASM and Its Application in Facial Feature Points Detection

    • 摘要: ASM(active shape model)是目前最流行的人脸对齐方法之一.为提高ASM在非均匀光照下多表情的人脸特征点检测的准确率,提出了一种融入Gabor特征、并将局部ASM和全局ASM结合的多模板ASM方法.人脸有丰富的表情,如微笑、惊讶、生气、发呆等等.就眼睛而言,可分为睁眼和闭眼;就嘴巴而言,可分为张大的嘴、微笑的嘴、O型的嘴(惊讶时)和紧闭的嘴.眼睛的这两种状态以及嘴巴的这4种状态使得形状有较大的非线性变化,不能简单地放在同一个线性模型下处理.分别对眼睛建立两个局部模板,对嘴巴建立4个局部模板,以及对整脸建立全局模板.在给定眼睛两个内眼角和嘴巴两个外嘴角的前提下,新方法首先用全局模板粗略确定眼睛所在区域,然后在此区域用眼睛的两个局部模板以及Hausdorff距离判断眼睛状态,同理可检测嘴巴状态,最后调用相应的全局模板去搜索整脸轮廓.实验表明,提出的方法其检测准确率比标准ASM有明显提高.

       

      Abstract: Active shape model is one of the most popular methods for facial image alignment. To improve its accuracy in facial feature points detection in facial images with various expressions and under nonlinear illumination, a multi-template ASM method, which integrates Gabor features and combines local ASM and global ASM, is proposed in this paper. Human faces often have various kinds of expression, such as smiling, surprising, anger, being confused and so on. For eyes, it can be open or closed, while for mouths, it can be smiling, widely open, tightly closed and “O” shape with surprise. Such two different kinds of eye states and four various kinds of mouth states give great nonlinear transformation to their ordinary shapes. Therefore, they can’t be processed simply in a single model. In this paper, two local templates for eyes, four local templates for mouths, and some global templates for the whole face are created. Under the assumption that the locations of two inner corners of eyes and two outer corners of mouths are known, in the new method, the approximate area for the two eyes is found first, and then the state of eyes in this area is determined by using the eyes local templates and the Hausdorff distance. Similarly, the state of the mouth can also be known. Finally the whole face contour is searched by global template corresponding to the estimated eyes and mouth states. The experiment shows that the method can achieve much higher detection rate than the standard ASM method.

       

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