CASIA OpenIR  > 毕业生  > 硕士学位论文
人脸自动检测
邓惠民
Subtype工学硕士
Thesis Advisor刘迎建
2001-06-01
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
Keyword人脸检测 人脸识别 视觉注意 Susan算法 多尺度分析 方向图 知识与规则 Human Face Detection Human Face Recognition Visual Attention Susan.multi-scale Analysis.direction Diagram.knowledge And Rules
Abstract本文提出了一种基于局部模式匹配的人脸检测和识别模型和一种基于方向 场的人脸检测模型。 前者主要思想是:通过检测人脸初始关键特征点,用局部模式匹配方法检测 出其中属于人脸的特征并进行识别。特征点的检测采用了基于注意机制的关键特 征点方法和SUSAN特征检测方法。预注意阶段的特征提取应用了竞争合作机制, 还采用了多尺度小波分析,以消除纹理的影响。SUSAN特征检测方法对自然图 像有很好的稳定性和准确性。我们用明视变换得到各特征点的局部模式,并予以 表象,通过训练用KL变换压缩局部模式并记忆下来。然后用待识别模式和记忆 的模式比照,识别出各个特征点的属性。我们的方法中识别的过程类似检测的过 程,但我们分为两级匹配,即各特征点审问他置的整体图匹配和各对应特征点局 部模式的匹配。 后者主要思想是:通过计算图像的方向图,利用人脸在方向图上的独特性, 根据一些规则搜索方向图来确定人脸的两部分区域,再予以组合就得到人脸图 像。人脸在方向图上类似一个封闭多边形(一般是六边形),我们将其拆分成两 部分分别予以考虑,来获得两类特征区域。其中某些规则的确立需要用到一些简 单知识。这是一种全新的方法,速度极快,实验结果令人鼓舞。 这两类方法都具有一定的实用性。
Other AbstractA local patterns matching based human face recognition model and a oriental field based face detection model are presented. In the former, we detect the initial key features of a face image. Through local patterns matching, we get the true features that belongs to a human face. Then we can use them for face recognition. We use two methods to detect features, one is based on attention, the other is SUSAN. The former uses cooperation-competition mechanism to detect saliency feature points and uses multi-scale analysis to remove the effect of the texture. The latter is a new method for natural image processing, with very good veracity and stability. We use photopic map to get the local patterns of each feature point, and then represent the local patterns. We use KL transform to compress tile local patterns and memorize them. Then we match the pending local patterns with the memorized local patterns to decide which kind of patterns they fall into. The procedure of recognition is similar to the detection in our method. But we use two-grade matching, the matching of each local patterns and the matching of the space relations among these patterns, In the latter, we calculate the direction diagram and use the character of a human face in a direction diagram, according to some rules we present, we search the direction diagram to get the two feature parts of each face. Combining the two parts: we get each face in an image. The human face in a direction diagram is like a closed polygon(hexagon often). We consider two parts of it and get two kinds of feature areas. Some rules used are based on simple knowledge. It's a totally new and very quick method, the experiment results are quite exciting. The two methods both have some practicability.
shelfnumXWLW607
Other Identifier607
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6858
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
邓惠民. 人脸自动检测[D]. 中国科学院自动化研究所. 中国科学院研究生院,2001.
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