资源列表
two_phase_sparse_ORL
- 两阶段测试样本稀疏表示方法具有识别率高的特点，有助于准确分类测试样本，但稀疏方法迭代时间长，效率较低，因此仍需要与其他方法进行结合-Two-stage test sample sparse representation method has high recognition rate, helps to accurately classify the test samples, but sparse iterative approach for a long time, less efficie
2413
- 广义的人脸识别实际包括构建人脸识别系统的一系列相关技术，包括人脸图像采集、人脸定位、人脸识别预处理、身份确认以及身份查找等；而狭义的人脸识别特指通过人脸进行身份-Construction of broad recognition, including face recognition system actually a series of related technologies, including facial image capture, face detection, face reco
text
- 眼睛提取,能识别出眼睛，通过调试可以用。包含cpp文件，还有注释说明-Eye extract, can identify the eye, can be used by debugging
manmotiondetect
- 人类动作识别，使用的是c++和opencv开发，有多种识别方法，建议收藏-Human movement recognition, using a c++ and opencv development, there are a variety of identification methods, the proposed collection of
HandGestureRecog
- 结合OpenCV，实现人手势的识别与跟踪。-combine with OpenCV,the project realizes the hand gesture dectect and tracking.
Detect100227a
- visual c++ 人脸检测程序，可以检测图片中的人脸。必须安装opencv才能运行。-visual c++ face detection program that can detect faces in the picture. Opencv must be installed to run.
yanjiaojiance
- 人的眼角定位，眼角的定位对于人脸图像的预处理和人脸识别有很大作用-Human eye position, eye position for face image preprocessing and recognition of a significant role in
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- 眼睛提取,能识别出眼睛，通过调试可以用。包含cpp文件，还有注释说明-Eye extract, can identify the eye, can be used by debugging. Cpp file that contains, as well as explanatory notes
Usingskincoloregmentationandsymmetrytransformation
- 利用肤色分割和对称变换实现鲁棒人脸特征-Using skin color segmentation and symmetry transformation used to deliver a robust facial feature symmetry transform skin color segmentation and facial feature location using robust skin color segmentation and symmetry transform r
OpenCVDrawContours
- 本程序是基于OpenCV的轮廓提取函数，有兴趣的可以-This procedure is based on the OpenCV function of the contour extraction, interested can look at
motiondetection
- this motion dectection sample-this is motion dectection sample
shoushijiasudu
- 通过三轴加速度传感器采集的人书写0-9数字的加速度信号，供300组，可用于手势识别分类原始数据-The acceleration signal of the 0-9 digital signal collected by the three axis acceleration sensor is provided for the 300 groups, which can be used for the classification of gesture recognition.