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Description: The original source codes works on morphing two people faces as a whole and then combine them by cross dissolve. In this project, I have modified the code so that it works on one face and morph partially on the face, such as the mouth, left eye and right eye.-The original source codes works on morphin g two people faces as a whole and then combine the m by cross dissolve. In this project, I have modified the code so that it works on one fa ce and morph partially on the face, such as the mouth, left eye and right eye.
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Size: 19456 |
Author: sjtuzyk |
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Description: 用Matlab写的投影法提取嘴唇
输入图像必须是规定大小的人脸-Written using Matlab projection extraction lips input image must be provided for the size of face
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Size: 1024 |
Author: 风之子 |
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Description: vc编程，用两个不同的方法实现人眼，鼻子和嘴的定位-vc programming, with two different methods to achieve the human eye, nose and mouth positioning
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Size: 3688448 |
Author: wangxiang |
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Description: 在YCbCr通道上，对人的嘴唇的寻找，通过大量数据样本得到的嘴唇颜色区域，效果不错，这个程序只是在静态图片里寻找，对做嘴形识别的人有帮助-Channel in the YCbCr on the lips of people search through a large amount of data samples to be the color of the lip region, the effect is true that this procedure only to find a static picture of the so-shaped mouth to help people identify
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Size: 89088 |
Author: richard |
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Description: High information redundancy and correlation in face images result in efficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.-High information redundancy and correlation in face images result in inefficiencies when such images are used directly for recognition. In this paper, discrete cosine transforms are used to reduce image information redundancy because only a subset of the transform coefficients are necessary to preserve the most important facial features such as hair outline, eyes and mouth. We demonstrate experimentally that when DCT coefficients are fed into a backpropagation neural network for classification, a high recognition rate can be achieved by using a very small proportion of transform coefficients. This makes DCT-based face recognition much faster than other approaches.
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Size: 25600 |
Author: mhm |
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Description: 这是一篇关于图象中眼睛和嘴巴的检测与定位的文章-This is an image in the eyes and mouth on the detection and location of the article
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Size: 4986880 |
Author: wangbo |
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Description: Perfect matlab facetracker, detects eyes, mouth and face.
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Size: 9216 |
Author: stein |
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Description: Matlab平台下在人脸区域利用EyeMap和MoutMap算法检测眼睛-Matlab platform in the face region detection algorithm using EyeMap and MoutMap eyes
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Size: 1024 |
Author: jiangshui |
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Description: 主要是连通分量提取及实现,通过matlab实现的了在人脸局部图像中定位嘴的中心.-Mainly connected component extraction and realization, through matlab to achieve in the face of local images to locate the center of the mouth.
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Size: 1024 |
Author: tianwenxu |
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Description: 在所给定的图片上自动标定出嘴的位置，方便不同图像嘴的定位-In the picture given by the location of automatic calibration of the mouth, mouth to facilitate the positioning of different images
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Size: 49152 |
Author: 秦刚 |
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Description: 在人脸局部图像中定位嘴的中心。MATLAB环境代码，配有实验用图。具体步骤：对输入图像进行二值化处理-标注二值图像中的连通分量-找出最大的连通分量-计算最大联通分量中心。《精通Matlab数字图像处理与识别》-The face part image is positioned in the center of the mouth. MATLAB environment code, with experimental Fig. Specific steps: input image binarization processing- marked binary images connected components- find the largest connected component- component to calculate the maximum Unicom center. " Mastering Matlab digital image processing and recognition."
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Size: 3072 |
Author: 廖欣 |
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Description: Lets see how to detect face, nose, mouth and eyes using the MATLAB built-in class and function. Based on Viola-Jones face detection algorithm, the computer vision system toolbox contains vision.CascadeObjectDetector System object which detects objects based on above mentioned algorithm.
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Size: 225280 |
Author: sirisha |
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Description: it is a matlab code for facial objects like face,nose,eyes and mouth detection
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Size: 386048 |
Author: Uzair ahmed |
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Description: Automatic detection of eyes,nose and
mouth in an image using inbuilt matlab
functions
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Size: 1024 |
Author: backspacekb |
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Description: This a matlab code for cropping the local parts(left eye,right eye,nose,mouth)-This is a matlab code for cropping the local parts(left eye,right eye,nose,mouth)
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Size: 1828864 |
Author: Akshay Tiwari |
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Description: matlab 串口显示程序！可以接受产口发送的数据来显示！-matlab serial display program! You can accept the data sent to the display-mouth!
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Size: 9216 |
Author: duqigong |
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Description: ASM算法 MATLAB源代码
人脸特征点定位的目的是在人脸检测的基础上，进一步确定脸部特征点（眼睛、眉毛、鼻子、嘴巴、脸部外轮廓）的位置。定位算法的基本思路是：人脸的纹理特征和各个特征点之间的位置约束结合。-The purpose of the facial feature point positioning is to further determine the position of the facial feature points (eye, eyebrows, nose, mouth, contour of the face) on the basis of face detection. The basic idea of the localization algorithm is that the texture features of the face and the position constraint between the individual feature points are combined. The classical algorithm is ASM and AAM.
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Size: 152576 |
Author: 曾 |
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Description: 编写M文件，计算以下问题：
口口口口x口=口口口口
以上九个口代表1~9这九个数字，不得遗漏或重复。(Write M file, calculate the following questions:ABCD x N=EFGH
More than nine mouth on behalf of the 1 ~ 9 nine Numbers, not omission or duplication.)
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Size: 13312 |
Author: Jenny Zeng
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Description: 一本关于matlab口碑很好的入门书籍，对于初学者大有裨益，值得一看。(A good introduction book about matlab word-of-mouth, for beginners, it is worth reading.)
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Size: 7383040 |
Author: 郁闷的土豆 |
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Description: 本设计为基于MATLAB的疲劳检测识别，可应用于疲劳驾驶监测，专注度检测等应用。本设计带有GUI可视化界面，自行录制好视频后，读取视频，分帧，读取每一帧影像，计算其眼睛张合度及嘴巴张合度，通过这2个参数来判断是否疲劳。(This design is based on MATLAB fatigue detection and recognition, can be applied to fatigue driving monitoring, concentration detection and other applications. This design has a GUI visual interface. After recording the video, the video is read, divided into frames, and each frame is read. The eye opening and mouth opening degree are calculated, and the fatigue is judged by these two parameters.)
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Size: 167936 |
Author: 可乐一生 |
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