An optical processor for high speed human face recognition is designed.
设计了一种用于快速人脸识别的光学协处理器。
A complete Human Face Recognition System should include Human Face Detection, Feature Extraction, and Match Recognition.
一个完整的人脸识别系统包括人脸检测、特征提取、以及匹配识别。
Due the complex human face patterns, facial features localization is an important technique for automatic human face recognition.
对于复杂的人脸模式，脸部特征定位是人脸自动识别技术的关键。
Human face recognition is an important subject in the area of pattern recognition, which has a wide range of potential applications.
人脸识别是模式识别研究领域的重要课题，具有广阔的应用前景。
Face detection is an important step in many applications such as human face recognition, video conferencing, human computer interfacing etc.
人脸检测在许多应用中都是重要的一个处理阶段，例如人脸识别、电视会议、人机界面等。
Describes experimental studies of human face recognition performance and recent attempts to mimic this ability in artificial computational systems.
描述关于人类脸孔辨识反应的实验研究与近来在人工计算系统上对此能力的模拟。
Human face problems consist of four parts: human face detection, human face tracking, human face recognition and the derived analysis of pose and expression.
人脸问题主要包括：人脸检测、人脸跟踪、人脸识别，以及其衍生出来的姿态和表情分析四个应用领域。
Absrtact: Research of human face recognition is an important topic in the area of pattern recognition and artificial intelligence, and it has very broad application prospects.
摘要：人脸识别的研究是模式识别和人工智能领域内的重要课题，有着十分广泛的应用前景。
An optical image recognition system based on the volume holographic storage technology is constructed. It is applied to an "electronic guard" system based on the real time human face recognition.
构建了基于体全息存储技术的光学图像识别系统，应用在以实时人脸识别为基础的电子门卫系统中。
The paper proposes a design and implementation of an embedded system of human face recognition, it includes the frame of hardware, the arithmetic of face recognition, its driver and its application.
本文提出了一种嵌入式人脸识别系统的设计及具体实现方法，其中包括硬件结构、人脸识别算法、驱动以及其应用程序的实现。
Human face recognition has become a research focus in pattern recognition, because it is a most development potential biometric technology for the characteristics of non-contact, safe and convenient.
作为极具应用价值的生物特征识别技术，人脸识别有着无接触、快速及安全等优势，其也一直是模式识别的研究热点。
The robots will augment their human users, enhancing their senses by offering capabilities like better vision and hearing as well as futuristic skills like face recognition.
通过提供更好的视觉和听力这样的能力以及面部识别这样的未来技能来提高他们的感官能力，这些机器人将增强它们人类用户的能力。
Due to its complexity, it is difficult to describe the rules of human face detection and recognition.
人脸的检测和识别是一个非常复杂的问题，对它的许多规律和规则进行显性的描述是相当困难的。
The feature of skin color is an important feature of human being, which plays a key role in human face detection and recognition, objectionable image filtering based on content, etc.
肤色特征是人体表面的重要特征，在人脸检测与识别、基于内容的不良图像过滤系统中有着重要的地位。
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.
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。
A face recognition approach correlative with poses is presented for recognizing pose varied human faces.
针对多姿态人脸识别的情况提出了一种姿态相关的人脸识别方法。
The eigen skin-color method is for the color images. For gray images, this paper USES face recognition method based on hidden Markov models to detect human faces.
特征肤色的方法是针对彩色图像的人脸检测方法，针对灰度图像本文采用基于隐马尔可夫模型的人脸识别方法来检测人脸。
Being a primary phase of face recognition, vision point tracing, and face image compression etc., inspecting human face out from the image background is the very first step.
作为人脸识别的重要的第一步，人脸检测所做的工作是将人脸从图像背景中检测出来，它是人脸识别、视点跟踪和人脸图像压缩等应用中的重要环节。
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。
Finally, it studies the application of the edge detection in human face detection and recognition.
最后通过实例研究了人脸边缘检测在人脸检测和识别中的具体应用。
Human facial features positioning is a key stage in face recognition and the accuracy of the positioning directly relates to the reliability of subsequent applications.
人脸部特征点的定位是人脸识别中的关键步骤，定位准确与否直接关系到后续应用的可靠性。
This approach would help to extract the vital feature points on human face automatically and improve the accuracy of face recognition.
眼角的自动定位能够给后续的人脸特征自动提取和识别算法研究奠定良好的基础，帮助提高人脸识别算法的识别率。
Based on the analysis of human face in ID card, this paper proposes a new face recognition method, which integrates the geometric eigenvector matching with the weighted face subdivision matching.
在仔细分析证件照片中人脸特点的基础上，提出了一种把人脸的几何特征矢量匹配和人脸的分块加权匹配相结合的思想。
Finally, this method is used to solve the recognition problem of human face images which is one of the most difficult problems in pattern recognition.
最后，我们将此方法用于解决图象识别中非常困难的人像识别问题。
Best viewpoint selection in multiple cameras plays an important role in many applications such as human-machine interaction, videoconference, and face recognition in sequence images.
多摄像机环境中的人脸最优视角选择在多通道人机交互，视频会议，序列图像中的人脸识别等领域有着广泛的应用。
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。
Use the image illumination correction, reduce the dimension of face images and different lighting conditions, the use of human face images improved the BP neural network for recognition.
运用了图像进行光照校正，人脸图像进行降维及不同的光照条件下的人脸图像运用改进型的BP神经网络对进行识别。
Study on face, iris and ear multi-biometric feature fusion and recognition belongs to a leading task about human perception nature and rule.
人脸、虹膜与人耳等多生物特征融合与识别的研究属人类认知本质与规律的前沿课题。
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.
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.
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。
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