中文摘要：

人脸轮廓的定位提取,是计算机视觉领域的新兴热点研究课题.该课题对于人脸识别、表情识别、目标跟踪等诸多相关课题的研究具有重要意义.特征点是目前人脸轮廓的最主要描述形式.近年来,伴随着受关注度的不断提升,针对人脸特征点定位技术的研究获得了长足的发展.文中对过去十年间该方向上出现的新方法和新技术进行了整体综述.具体包含以下内容：（1）介绍了人脸轮廓描述形式、所采用的图像特征、实验图像数据集等相关知识;（2）按照核心技术方法的区别,所有方法被进行具体细分并归类介绍;（3）统计汇总分析了各方法的实施细节,包括特征点数目、实验数据集、图像特征形式、方法相对实验精度等内容;（4）分析了近年来方法发展的趋势和共性特点;（5）对目前研究中亟待解决的挑战性问题进行了讨论.

英文摘要：

Face shape localization is a newly-developed hot research topic in the area of computer vision.It is of great value to many related research topics such as face recognition,emotion recognition,object tracking and so forth.The feature points are the most important representation method to face shape at present.In the past few years,along with the rise of interested attentions,the research about face feature points extraction has achieved considerable development.In this paper,a review is conducted about the novel methods and techniques of face feature points extraction invented in the past ten years.It is composed by the following contents.（1）Related information and knowledge such as shape description,adopted image feature,experimental image datasets,are comprehensively introduced.（2 ）All related approaches are classified and introduced in detail according to the distinction of core underlying techniques.（3）Some details of approach implementation are summarized and explored such as,the number of feature points,experimental datasets,feature formalization,relative experimental accuracies and so on.（4）The developingnbsp;tendencies and common characteristics of recent approach development are discussed.（5）A few of challenging problems faced by current researches are discussed.