而人脸检测技术由干在一定的正确率下可以远距离检测目标，越来越得到人们的重视。
Since face tracking and recognition technology could detect object in a certain distance with an ideal accuracy, it gets more attention and application in security fields.
本文首先介绍了人脸检测技术的研究背景和意义，以及目前比较常用的一些人脸检测算法。
Firstly this paper introduces the face detection technology research background and significance, and the current number of commonly used face detection algorithm.
本文采用图像识别——人脸检测技术来获取客流量分布，即对实时获取的图像进行分析，获取人脸的个数。
In this thesis the distribution is obtained by using the technology of face detection, namely the number of faces in real time images.
本文首先在对人脸检测、人脸面部特征定位技术的相关文献进行综述的基础上，提出了人脸检测技术融合算法。
In this thesis, I present a novel face detection framework based on a face detection algorithm merged with some advanced algorithms.
此外，人脸检测技术有助于把他们每个人都面临着最好的，而超级平稳摄像光学图像稳定系统有助于确保图像仍然尖锐和正确的。
Additionally, face Detection technology helps everyone put their best face forward, while the Super SteadyShot optical image stabilization system helps ensure images remain sharp and true.
本文在总结和分析现有人脸检测技术的基础上，重点研究了基于矩形特征的人脸检测技术及以此为基础并结合运动信息的动态人脸检测技术。
Relying on the analysis of existed face detection techniques, this paper mainly describes face detection based on rectangle feature and dynamic face detection combined with motion information.
人脸检测与标定技术是人脸识别技术中的核心课题。
The Technique of Face Detect and Demarcating is a key problem of the Face Recognition.
近些年来，人脸检测识别技术逐渐成为最具潜力的身份验证手段。
In recent years, face detection and recognition technology has become the most promising means of authentication.
人脸检测与识别技术是利用生物特征技术进行个人身份鉴定的一种重要手段。
Face detection and recognition technology is an important method for identity authentication using biometrics.
研究了利用颜色直方图、颜色边缘幅值和边缘方向直方图特征，基于支撑向量分类器的检测人脸技术。
This paper studies the human face detection by support vector classifier using histograms of color, color edge and its orientation.
人脸检测与识别技术是模式识别、计算机视觉领域内具有理论价值和应用前景，且极具挑战性的研究课题之一。
Face detection and recognition technique is one of the most important and practical issue in the field of pattern recognition and computer vision.
本文采用的技术包括：皮肤检测、人脸检测、目标区域分割、敏感图像特征提取、分类器设计及过滤器在浏览器上的实现等。
Some key techniques are included, such as skin detection, face detection, object area segmentation, image features extraction, the design of classifier and the implement of filter based on browser.
人眼检测和定位是人脸识别技术中一个重要组成部分。
The detection and location of eyes is a very important part of face recognition.
人脸识别是模式识别与计算机视觉、生物识别技术的交叉学科，而人脸检测是人脸识别系统的关键环节。
Human face automatic recognition system is a cross subject combined with pattern recognition, computer vision and biometrics, in which human face detection is a key factor.
对人脸图像检测与识别技术的研究现状进行简要论述，并自行设计一个人脸特征自动提取系统。
This paper examines the research situation on face image detection and recognition and designs a facial feature automatic extract system.
本文通过对人脸检测与识别技术的研究，提出了一种利用眼睛梯度特征的人脸检测方法并对主成分分析方法做了改进以进行人脸识别。
Through studying the face detection and recognition technique, this thesis presents a method of face detection based on eyes feature and improves the PCA to recognize human face.
本文主要研究了视频中的人脸检测及跟踪技术。
In this thesis, a study on face detection and tracking in video is presented.
人脸检测作为人脸信息处理中的一项关键技术，近年来成为模式识别与计算机视觉领域内一项受到普遍重视、研究十分活跃的课题。
As a key technology for information processing, face detection has become a popular area of importance, very active research topic in Computer Vision and Pattern Recognition in recent years.
人脸识别系统主要包括两个技术环节：首先是人脸检测和定位，然后是对归一化的人脸图像进行特征提取与识别。
Two key techniques accounts the most for a human-face recognition system: one is face detection and orientation; the other is feature abstraction and recognition from unified human-face image.
人脸检测与人脸跟踪技术是各种人脸图像处理算法的关键技术。
The face detection and tracking are one of the key techniques in various facial processing algorithms.
人脸检测与识别技术是人工智能和机器视觉领域内最具挑战性的研究课题之一。
The automatic recognition and detection of human face is one of the most interesting and challenging topics in the fields of Artificial Intelligence and Computer Vision.
本发明公开了一种基于人脸生理性运动的活体检测方法及系统，属于人脸识别技术领域。
The invention discloses an in vivo detection method and a system based on the physiological motion of face, pertaining to the face recognition field.
对运动区域（视频前景），基于小波分析技术实现视频图像的人脸检测，进而引入改进的人脸模型进行高效的压缩编码；
Following, a wavelet based face detection algorithm is presented for the moving regions (foreground video objects), and an amendment for face model within MPEG-4 is introduced.
对运动区域（视频前景），基于小波分析技术实现视频图像的人脸检测，进而引入改进的人脸模型进行高效的压缩编码；
Following, a wavelet based face detection algorithm is presented for the moving regions (foreground video objects), and an amendment for face model within MPEG-4 is introduced.
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