搜索资源列表
yandingwei
- 一些有参考价值 文章关于人脸识别方面的．如果你还没有大量阅读 文章那就快看看这些吧，对你会有帮助的.次篇是关于人眼睛定位-some reference to the article on the value of face recognition. If you have not read the article would be a lot faster to see it, you have to help. Meeting people on the part of the eye loc
20077419401162
- 虹膜识别 基于 ARM的 嵌入式 自动追踪眼睛 识别虹膜
FaceDetection2
- 人脸识别，基于EMGU.CV做的，可以识别出人脸以及眼睛的位置。-Face recognition based on EMGU.CV done, you can identify the location of human face and eyes.
detecteyebmp
- 自动识别人脸上眼睛所在位置，从文件中读取图像，然后将处理后的图像存放到所要求的位置上。-Automatic Identification of human face location of the eyes, read from the document image, and then the images will be treated to the required storage location.
c02
- 人脸识别的程序，自己新做的！有需要的去看看吧。眼睛定位-Face recognition process, his new do! Need see it. Eye location
c03a
- 人脸识别的程序，自己新做的！有需要的去看看吧。眼睛定位-Face recognition process, his new do! Need see it. Eye location
EyeLocation
- 人脸识别和眼部定位 能都自动识别人脸，并定位一双眼睛-Face and eye positioning to automatically identify faces, and positioning a pair of eyes
human-face-recognition
- 本文提出了基于24位彩色图像对人脸进行识别的方法，介绍的主要内容是图像处理，它在整个软件中占有极其重要的地位，图像处理的好坏直接影响着定位和识别的准确率。本软件主要用到的图像处理技术是：光线补偿、高斯平滑和二值化。在识别前，先对图像进行补光处理，再通过肤色获得可能的脸部区域，最后根据人脸固有眼睛的对称性来确定是否就是人脸，同时采用高斯平滑来消除图像的噪声，再进行二值化，二值化主要采用局域取阈值方法，接下来就进行定位、提取特征值和识别等操作。经过测试，图像预处理模块对图像的处理达到了较好的效果，提
face-recognition
- 人脸识别，可以通过不同的算法提取人脸的不同部位，眼睛，鼻子，嘴巴等等！-Face recognition, can be extracted by different algorithms in different parts of the face, eyes, nose, mouth, and so on!
VCPP-human-recognise
- VC++ 人脸识别定位、眼睛、嘴巴和鼻识别-failed to translate
Face-and-Eye-Detection-Concept
- 这个示例代码提供了你这个概念对图像处理是使用EmguCV完成和操纵。一个好的例子图像处理是脸和目标检测和识别等,不过在此示例代码中我只给人脸检测和眼睛检测的概念-This sample code provides you the concept of image processing is to use EmguCV completed and manipulation. A good example of face image processing and target detection a
main2
- opencv 眼睛识别，脸部识别主程，有较好的鲁棒性-opencv eye recognition, face recognition, there is robust
HW07
- 人脸识别，眼睛，口识别，还附加了照片识别(Face recognition, eye, mouth recognition, and also attached photo recognition)
caffe-cvpr
- 显着区域检测是计算机视觉中长期存在的问题。它旨在找到最能吸引人眼睛注意的图像中的像素或区域。准确和可靠的显着性检测可以从视觉追踪和识别到图形图像处理等众多任务中受益。例如，成功的对象检测算法有助于自动图像分割，更可靠的对象检测，有效的图像缩略和重定位(Significant regional detection is a long-term problem in computer vision. It aims to find the pixels or regions of the most
face_detect_orgin
- 基于python人脸识别、眼睛认别。通过对人脸、眼睛特征分析分析，准确认别。(Face recognition and eye recognition based on python. Through the analysis of face and eye features, we can recognize them accurately.)