公开(公告)号：KR1020110067480A

公开(公告)日：2011-06-22

申请号：KR1020090124090

申请日：2009-12-14

Applicant: 한국전자통신연구원

Inventor： 안광호 ,  박소희 ,  정명진 ,  정윤수 ,  문기영

IPC: G06K9/00 ,  G06T7/40

CPC classification number: G06K9/00281 ,  G06K9/6212 ,  G06K9/6234 ,  G06K2009/4666

Abstract: PURPOSE: A feature points detecting method for detecting a face is provided to increase the accuracy of detecting a face by learning LBP feature points having various points and size. CONSTITUTION: A feature points detecting method for detecting a face comprises the steps of: assigning an initial value according to the kind of an input image, face image or non-face image(400); setting the weight value of the input image according to the number of face images and non-face images in the input images(S402); standardizing the weight value(S404); calculating an error value of the feature points using the weak learning machine for the feature points, the standardized weight value, and the initial value(S406); selecting a weak learning machine having a least error value(S408); checking whether the input image is determined accurately on the basis of the weak learning machine(S410); and changing the weight value depending on the check results(S416).

Abstract translation: 目的：提供用于检测脸部的特征点检测方法，以通过学习具有各种点和大小的LBP特征点来提高对脸部的检测精度。 构成：用于检测面部的特征点检测方法包括以下步骤：根据输入图像的种类，面部图像或非脸部图像（400）分配初始值; 根据输入图像中的脸部图像和非脸部图像的数量来设置输入图像的权重值（S402）; 标准化重量值（S404）; 使用弱学习机计算特征点的误差值，标准化权重值和初始值（S406）; 选择具有最小误差值的弱学习机（S408）; 基于弱学习机检查是否准确地确定输入图像（S410）; 并根据检查结果改变重量值（S416）。