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Description: 我们给出一个模板 和一幅图象 。不难发现原图中左边暗，右边亮，中间存在着一条明显的边界。进行模板操作后的结果如下： 。
可以看出，第3、4列比其他列的灰度值高很多，人眼观察时，就能发现一条很明显的亮边，其它区域都很暗，这样就起到了边沿检测的作用。
为什么会这样呢？仔细看看那个模板就明白了，它的意思是将右邻点的灰度值减左邻点的灰度值作为该点的灰度值。在灰度相近的区域内，这么做的结果使得该点的灰度值接近于0；而在边界附近，灰度值有明显的跳变，这么做的结果使得该点的灰度值很大，这样就出现了上面的结果。
这种模板就是一种边沿检测器，它在数学上的涵义是一种基于梯度的滤波器，又称边沿算子，你没有必要知道梯度的确切涵义，只要有这个概念就可以了。梯度是有方向的，和边沿的方向总是正交(垂直)的，例如，对于上面那幅图象的转置图象，边是水平方向的，我们可以用梯度是垂直方向的模板 检测它的边沿。
例如，一个梯度为45度方向模板 ，可以检测出135度方向的边沿。-we give a template and an image. It is not difficult to find the maximum were left dark, right-liang, in the middle there is a clear boundary. After the template for the operation results are as follows :. Can be seen, three, four out other than the gray value is much higher, eye observation, we can obviously found a bright side. Other regions are dark, and this has played a role in the detection of 2500. Why is this the case? A closer look at the template on which to understand it. It means the right to the point o gray minus left point as a gray value of the point of gray values. In a similar gray area, do so as a result of the point of gray values close to 0; And near the border. gray values jump significantly changed, the results do make the point very gray value, and this appeared to
Platform: |
Size: 9333 |
Author: 李涯 |
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Description: createiristemplate - generates a biometric template from an iris in
％ an eye image.
％
％ Usage:
％ [template, mask] = createiristemplate(eyeimage_filename)
％
％ Arguments:
％ eyeimage_filename - the file name of the eye image
％
％ Output:
％ template - the binary iris biometric template
mask - the binary iris noise mask
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Size: 1491 |
Author: wpf |
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Description: 一个由zafersavas于2008年完成的完全基于VC++6实现的人脸检测和人眼跟踪程序，通过设置相应的参数实现不同的功能。人脸跟踪中使用了camshift算法和Haar算法，眼睛检测中使用了自适应PCA算法和模板匹配算法，还支持文件和网络摄像头两种输入方式，经过试验，检测速度比较快和准确度也比较高。附带demo程序。 使用步骤： 菜单TrackEye Menu --> Tracker Settings 输入源Input Source: video 选择文件输入指定为： ..\Avis\Sample.avi 人脸检测算法（Face Detection Algorithm）: Haar Face Detection Algorithm 选中 “Track also Eyes” checkBox 眼睛检测算法（Eye Detection Algorithm）: Adaptive PCA 取消选择 “Variance Check” Number of Database Images: 8 Number of EigenEyes: 5 Maximum allowable distance from eyespace: 1200 Face width/eye template width ratio: 0.3 ColorSpace type to use during PCA: CV_RGB2GRAY 瞳孔检测设置（Settings for Pupil Detection） Check “Track eyes in details” and then check “Detect also eye pupils”. Click “Adjust Parameters” button: Enter “120” as the “Threshold Value” Click “Save Settings” and then click “Close” Settings for Snake Check “Indicate eye boundary using active snakes”. Click “Settings for snake” button: Select ColorSpace to use: CV_RGB2GRAY Select Simple thresholding and enter 100 as the “Threshold value” Click “Save Settings” and then click “Close”
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Size: 204022 |
Author: sichuanlu |
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Description: 我们给出一个模板 和一幅图象 。不难发现原图中左边暗，右边亮，中间存在着一条明显的边界。进行模板操作后的结果如下： 。
可以看出，第3、4列比其他列的灰度值高很多，人眼观察时，就能发现一条很明显的亮边，其它区域都很暗，这样就起到了边沿检测的作用。
为什么会这样呢？仔细看看那个模板就明白了，它的意思是将右邻点的灰度值减左邻点的灰度值作为该点的灰度值。在灰度相近的区域内，这么做的结果使得该点的灰度值接近于0；而在边界附近，灰度值有明显的跳变，这么做的结果使得该点的灰度值很大，这样就出现了上面的结果。
这种模板就是一种边沿检测器，它在数学上的涵义是一种基于梯度的滤波器，又称边沿算子，你没有必要知道梯度的确切涵义，只要有这个概念就可以了。梯度是有方向的，和边沿的方向总是正交(垂直)的，例如，对于上面那幅图象的转置图象，边是水平方向的，我们可以用梯度是垂直方向的模板 检测它的边沿。
例如，一个梯度为45度方向模板 ，可以检测出135度方向的边沿。-we give a template and an image. It is not difficult to find the maximum were left dark, right-liang, in the middle there is a clear boundary. After the template for the operation results are as follows :. Can be seen, three, four out other than the gray value is much higher, eye observation, we can obviously found a bright side. Other regions are dark, and this has played a role in the detection of 2500. Why is this the case? A closer look at the template on which to understand it. It means the right to the point o gray minus left point as a gray value of the point of gray values. In a similar gray area, do so as a result of the point of gray values close to 0; And near the border. gray values jump significantly changed, the results do make the point very gray value, and this appeared to
Platform: |
Size: 9216 |
Author: 李涯 |
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Description: 这个是我这网上下的,它是一种改进的模板匹配眼睛定位方法,希望对大家有所帮助!-This is my under-line, it is an improved template matching method of positioning the eyes, and they hope to be helpful to everyone!
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Size: 161792 |
Author: 张龙 |
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Description: 人脸检测的vc++程序,采用肤色模板,人眼和嘴巴的定位,效果较好-Face Detection vc++ Procedures, the use of color template, the human eye and mouth positioning, better
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Size: 64512 |
Author: fanchao |
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Description: createiristemplate - generates a biometric template from an iris in
％ an eye image.
％
％ Usage:
％ [template, mask] = createiristemplate(eyeimage_filename)
％
％ Arguments:
％ eyeimage_filename - the file name of the eye image
％
％ Output:
％ template - the binary iris biometric template
mask - the binary iris noise mask-createiristemplate- generates a biometric template from an iris in an eye image. Usage: [template, mask] = createiristemplate (eyeimage_filename) Arguments: eyeimage_filename- the file name of the eye image Output: template- the binary iris biometric template mask- the binary iris noise mask
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Size: 1024 |
Author: wpf |
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Description: 人眼定位的matlab代码，使用模板匹配的方法实现-The human eye positioning matlab code, using a template matching method
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Size: 2048 |
Author: 钱明 |
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Description: 人脸检测+眼睛检测（模版匹配）+瞳孔检测+嘴唇检测（cameshift）-face detection+ eye detection( template match)+pupil detection+lip detection (camshift)
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Size: 48332800 |
Author: briend |
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Description: When the user initially clicks the eye feature, a box is drawn around the square and the subimage within this square is cropped out of the image frame. The cropped image is used as a template to find the position of the feature in subsequent frames. The system determines the position of the feature using Sum of Square Differences (SQD) method. To reduce extensive computation, the system tracks the feature in a "search window", a small area around the position of the feature in previous frame.
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Size: 2048 |
Author: gaptek |
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Description: tracking eye using template matching algorithmj
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Size: 7168 |
Author: sajjad |
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Description: 一种改进的模板匹配眼睛定位方法的论文，值得学习。-An improved method of template matching eye positioning papers, worth learning.
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Size: 161792 |
Author: mao |
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Description: generates a biometric template from an iris in
an eye image.-generates a biometric template from an iris in
an eye image.
Platform: |
Size: 16384 |
Author: samira |
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Description: 基于模板匹配眼睛特征点定位算法，付费后得到的学习论文，值得参考。-Based on template matching algorithm for eye location, payment received after the study paper, worth considering.
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Size: 418816 |
Author: mao |
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Description: Tracking a user defined template in an image (such as user s eye) for computer vision application. Built using OpenCV
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Size: 16384 |
Author: nunwithagun |
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Description: 用模板匹配方法，实现的人眼定位，快速方便！-Using template matching method to achieve positioning of the human eye, quick and easy!
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Size: 30720 |
Author: 周涛 |
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Description: 提供一个基于模板相似度匹配法的人脸识别程序。-Provide a template matching method based on similarity of face recognition programs.
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Size: 1024 |
Author: mr deng |
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Description: after i run the code, it shows the picture k001.jpg, but it shows nothing about face detection or eyetracking, then i double-click the picture, the command window shows "Please Crop The Right Eye Template" , some body please tell me how to test this code, whether i miss the inputs of function "eyematch2"-- templates for left and right eyes, and how to get these templates, my email-address is ykaitao_best@126.com, i am very appreciate if someone can help me.
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Size: 18432 |
Author: umer javaid |
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Description: 动态跟踪人的眼睛，初学者可以下载学习，使用最大互相关算法实现模板与待测图像的配准-Dynamic tracking people' s eyes, beginners can download the study, using the maximum cross-correlation algorithm and tested template image registration
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Size: 2048 |
Author: 祥林 |
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Description: PTCMS3.0.2安装程序，自带快眼模板(Ptcms3.0.2 installation program, with its own fast eye template ptcms3.0.2 installation program, with its own fast eye template)
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Size: 4855808 |
Author: 雷佳 |
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