神奇的是Google图片搜索可以识别人脸，在浏览器地址栏搜索结果页面网址后面添加“ &imgtype=face ” 确定后Google会过滤掉所有不是人的图片。
Google Image Search recognises faces... add &imgtype=face to the end of the returned URL in the location bar, then hit enter to filter out pictures that aren't people.
设计了一种用于快速人脸识别的光学协处理器。
An optical processor for high speed human face recognition is designed.
论文提出了基于图像多路正交投影和最小距离分类器的人脸识别方法。
This paper proposes an image multi-orthogonal projection method for face recognition based on least class distance classifier.
文中使用小波变换来对人脸的高维图像矢量进行压缩，并设计了一个支持向量机分类器系统来识别人脸。
This article utilizes the wavelet transform to compress the high dimensional face image vectors, then devises an SVM classify system to recognition the face.
重点讨论了人脸表示、分类器的设计和复杂背景下快速人脸检测与识别系统架构问题。
The topics such as face representation, classifier design and the design of Face Detection and Recognition System for images with complex background are discussed in details.
首先基于差分图像和肤色信息检测出人脸，其次使用改进的奇异值分解方法提取面部特征，最后运用最小距离分类器进行识别。
First based on the difference image and the skin color the face is detected and localized, then features are extracted by using improved SVD, last the features is classified by minimal distance.
鉴于人脸识别问题的特殊性，将传统分类方法与人工神经网络方法结合起来，构造了一个混合分类器，从而极大地提高了识别率。
A hybrid classifier is formed by combining the traditional classification method with an artificial neural algorithm to significantly improve the rafe of recognition.
最后构造了一个层次的距离分类器进行人脸的识别。
Finally, a hierarchical distance classifier is designed to recognize human faces.
该处理器可以加速诸如手势识别、人脸匹配或表情跟踪，但并无意成为一个完整意义上的CPU。
The processor can accelerate tasks like hand gesture recognition, face matching or face tracking, but is not designed to be a full-fledged CPU.
这里特征提取是人脸识别的关键环节，有效的人脸特征提取方法不仅有助于简化后续的分类器设计，而且能够提高识别率。
Feature extraction is the key to face recognition. An effective feature extraction method not only helps to simplify the classification of follow-up design, but also can enhance the recognition rate.
最后将降维后的数据作为分类器的输入进行人脸分类识别。
Let the nature data structures as inputting for the classifier of the face classification.
本文提出了一种新的基于一维相关滤波器的类依赖特征分析人脸识别方法。
The results proved that the method of correlation filters presented in the paper is effective and feasible.
实验结果表明，利用此分类器结合本文提出的改进方法能进一步提高人脸识别率。
The experiments show that the proposed algorithm ND-LDA can achieve much higher recognition accuracy using the classifier based on Compressed Sensing theory.
实验结果表明，利用此分类器结合本文提出的改进方法能进一步提高人脸识别率。
The experiments show that the proposed algorithm ND-LDA can achieve much higher recognition accuracy using the classifier based on Compressed Sensing theory.
应用推荐