搜索资源列表
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C实现的基于adaboost算法的人脸检测程序及人脸库-C-based implementation adaboost algorithm face detection process and face
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是一个基于LBP特征的人脸检测算法，通过OPen cv自带的库文件运行程序，交流请联系chinaqinyh@163.com-Is based on LBP features face detection algorithm, OPen cv library file that comes with running the program, please contact chinaqinyh@163.com exchange
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是一个改进的haar特征的人脸检测算法，通过OPen cv自带的库文件运行程序，交流请联系chinaqinyh@163.com ，论文已经发表 ，请勿侵权-Haar feature is an improved face detection algorithm, OPen cv library file that comes with running the program, the exchange of contact chinaqinyh@163.com, papers have been
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人脸识别，基于svm算法检测人脸是否配戴眼镜-Face recognition, face detection algorithm based on svm whether to wear glasses
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opencv入门级C++程序代码调试，第三课：识别一张人脸二维静态图片，采用haar特征识别算法。-Opencv entry level debugging c++ program code, the third class: identification of a human face 2 d static image, using haar feature recognition algorithm.
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FDDB人脸数据集评估C++代码，从官网上下载的，拿来就能用，用于评估人脸检测算法检测率及误检率。-FDDB face data set to assess the C++ code, downloaded the official website, used to be able to use, for the assessment of human face detection algorithm detection rate and false detection rate.
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快速的人脸检测算法，基于肤色，MATLAB源代码-Fast face detection algorithm, based on skin color, MATLAB source code
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融合YCbCr肤色模型与区域标记的人脸检测算法研究-Fusion YCbCr color model and the research area of face detection algorithm
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基于opencv lbp的人脸检测算法，利用facedetect函数快速检测到人脸，提高检测速度，优化检测方法。-Face detection algorithm based on LBP facedetect, using OpenCV function to quickly detect human face, improve the detection speed, and optimize the detection method.
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本程序是基于肤色模型的人脸检测算法编写的代码，是在VS2010上面测试过可以使用的。-This procedure is based on the code color model face detection algorithm written in VS2010 tested above can be used.
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运用Adaboost算法haar分类器实现的人脸检测，帧率是32。-Using Adaboost face detection algorithm of Haar classifier, the frame rate is 32.
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用python语言实现的基于Harr特征的人脸检测算法，可以用于人脸的检测，眼睛，鼻子等脸部五官的检测-Using python language based on the Harr feature-based face detection algorithm can be used for the detection of face, eyes, nose and other facial features detection
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人脸检测识别与MATLAB实现，人脸检测算法，编程实现人脸图像分割-Face detection recognition and MATLAB implementation, face detection algorithm, programming to achieve face image segmentation
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经典的Haar-like+adboost级联训练的人脸检测算法-The classic Haar-like+adboost cascade training of face detection algorithm
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基于肤色的人脸检测算法，将彩色图像转换成Ycbcr图像，再根据肤色聚类 从而分割出人脸-Based on the skin color s face detection algorithm, the color image is converted to the image of Ycbcr, and the face is divided according to the color of the skin
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object detection using KLT algorithm
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人脸检测：
第一部分，使用Harr-like特征表示人脸，使用“ 积分图”实现特征数值的快速计算;
第二部分， 使用Adaboost算法挑选出一些最能代表人脸的矩形特征( 弱分类器)，按照加权投票的方式将弱分类器构造为一个强分类器;
第三部分， 将训练得到的若干强分类器串联组成一个级联结构的层叠分类器，级联结构能有效地提高分类器的检测速度。(Face detection:
In the first part, the Harr-like feature is used t
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face detection algorithm in matlab
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运用HOG提取人脸特征与支持向量机算法训练模型，进行人脸识别(Using HOG to extract facial features and support vector machine algorithm training model for face recognition)
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Viola-Jones 算法的人脸检测程序，附带检测图片(for detection using Viola-Jones Algorithm. To save Cropped Picture you need to change the folder location.)
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