搜索资源列表
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应用OpenCV的人脸识别，基于haar like cascade classifier-openCV face detection tutorial
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基于openCV的多角度人脸检测，融合了正脸侧脸haar分类器，具有极强鲁棒性-, The integration of multi-angle face detection based on openCV positive face side faces haar classifier, with strong robustness
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本程序实现了haar+adaboost人脸检测功能-Realized by the haar+ adaboost face detection function
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人脸检测的程序，用的haar特征和adboost算法，基于opencv的在VS2010上成功运行的C程序。可以检测静态图片，视频，和摄像头的视频中是否含有目标对象的程序。-Face detection program, with the the haar characteristics and adboost algorithm, based on opencv run successfully on VS2010 C program. The program can detect static
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人脸及行人检测中在opencv中要用到的haarcascade_righteye_2splits.xml，即特征检测的haar分类器，包括正面，侧边，上下左右各种，很全面-Face and pedestrian detection in opencv use to haarcascade_righteye_2splits.xml, feature detection haar classifier, including front, side, up and down various, very
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图像处理中人脸检测代码，并有主函数调用程序，采用Haar特征检测人脸。-Image processing human face detection code, and the main function of the calling program, Haar feature detection face.
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基于光流法的人脸追踪 先通过opencv的类haar特征检测人脸 然后用光流法筛选特征点并追踪-Optical flow method based face tracking to pass the class haar feature detection opencv face then light flow filter and track feature points
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基于opencv的人脸识别程序，基于haar的adoboost检测方法-Face recognition program based opencv，Adoboost based detection methods haar
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OpenCV Haar人脸检测静态化库函数，将xml文件静态化处理了，所以直接调用即可，无需xml文件了。-OpenCV Haar face detection static library functions, the static xml file processing, so you can directly call without xml files.
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基于OpencvHarr的kinect人脸检测-Face Detection through kinect camera with OpenCV Haar Method
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VS2013 OpenCV2.4.11人脸检测代码，该代码使用Haar特征分类器对图像中的人脸进行检测并圈出。-VS2013 OpenCV2.4.11 face detection code, the code USES the characteristics of Haar classifier to detect human faces in the images of the circle.
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Haar Cascade for face detection
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基于opencv的haar+adaboost训练器的人脸和人眼检测，带有训练好的xml文件。-Opencv based haar+ adaboost face and eye detection trainer, having trained xml file.
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使用opencv自带的haar特征分类器，进行人脸检测的程序代码。-A program with opencv inside classifier for face detection
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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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利用opencv进行人脸检测，运用了adaboost的haar特征-Use opencv face detection, the use of haar features adaboost
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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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通过opencv实现了对图像采用Haar特征实现中人脸检测的功能-Through the opencv realized of face detection in image using Haar feature implementation functions
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Python scr ipt to detect faces. It uses two haar cascade trained to recognise faces and eyes. The haar cascade are included. In uses OpenCV so it is required.
The scr ipt is written in Python 3.
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Normal Face detection source code using Haar Cascade Features in Python and C++
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