Description: 程序用matlab实现基于模板和肤色的人脸检测,首先利用肤色信息检测出可能的人脸区域,然后进行模板匹配.可以实现一幅图片中多人脸的检测.-procedures using Matlab based templates and color of face detection, the first to use color information may detect a face, then template matching. can be achieved over a picture of face detection. Platform: |
Size: 2353 |
Author:李守一 |
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Description: 程序用matlab实现基于模板和肤色的人脸检测,首先利用肤色信息检测出可能的人脸区域,然后进行模板匹配.可以实现一幅图片中多人脸的检测.-procedures using Matlab based templates and color of face detection, the first to use color information may detect a face, then template matching. can be achieved over a picture of face detection. Platform: |
Size: 2048 |
Author:李守一 |
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Description: 对由光源颜色变化引起的图像色彩偏差,进行了校正,并在YCbCr颜色空间建立了Cb-Cr色度查找表和亮度信息联合的肤色模型,应用预处理技术,去除部分非人脸区域,减少人脸检测的搜索空间,并采用模板匹配方法在人脸候选区域检测人脸.实验表明,该方法能够有效的从复杂环境的彩色图像中检测出左右旋转不超过45°的人脸,且不受人脸表情、尺度和数目的影响,且错误率较低.-Color by the light source caused by the change of image color deviation, a correction, and YCbCr color space established a Cb-Cr chrominance and luminance information look-up table of the color model of the joint application of pre-treatment technology, to remove some non-human face region, Face detection to reduce the search space, using a template matching method in the face candidate region detection of human faces. experiments show that the method can be effective in complex environments from color images detected no more than about 45 ° rotation of the human face, and from Facial Expression, scale and number of impact, and lower error rate. Platform: |
Size: 191488 |
Author:lll |
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Description: 这是一个用高斯模型来进行相似度计算
然后，采用模板匹配的算法实现人脸的检测和定位的。-This is a Gaussian model used for similarity computation and then, using a template matching algorithm of face detection and positioning. Platform: |
Size: 8192 |
Author:谭少侠 |
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Description: 本文考虑带旋转的人脸检测方法, 提出了一种基于颜色空间以及模板匹配的快速人脸定位方法。首先从常用的颜色空间中选
择出对光照因素稳健的肤色子空间, 然后基于该子空间进行肤色检测方法得到人脸大致区域, 最后采用模板匹配的方法确定人脸区域。
实验结果表明, 该方法速度快, 对于带角度旋转的人脸定位有很好的效果。-In this paper, we consider the face detection method with rotating a template matching fast face location method based on color space. First from the common color space is selected the healthy complexion subspace of illumination factors, skin detection method to obtain the approximate area of the face and then on the basis of the sub-space, and finally using the template matching method determines a face region. The experimental results show that this method is faster, and the rotation for the angled face positioning have a good effect. Platform: |
Size: 77824 |
Author:东方 |
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Description: 本文针对复杂背景下的彩色正面人脸图像,将肤色分割、模板匹配与候选人脸图像块筛选结合起来,构建了人脸检测实验系统,并用自制的人脸图像数据库在该系统下进行了一系列的实验统计。-Color frontal face images under complex background, skin color segmentation, template matching candidates face image block screening combined to build a face detection experimental system using a homemade face image database in the system series of experimental statistics. Platform: |
Size: 14336 |
Author:安静 |
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Description: Digital image face detection had been developing so much in this last decade. The searching for the best
method is still walking until today. This face detection research is using color model based segmentation method
combined with template matching. There are 4 main process in this research. First, motion detection is used to
minimize the size of the image by subtracting image n with image n+m. Then, by using YCbCr color model based
segmentation, the image is separated by skin color area and non-skin color area. Third, is to reduce the noise by
using the blurring way and by filtering its wide. The last one is matching the area that last with template that has
been prepared to detect which area is face. The result of the research, from 217 images and 10 videos , shows
that this method reach up to 70,5 face detection accuration procentage.-Digital image face detection had been developing so much in this last decade. The searching for the best
method is still walking until today. This face detection research is using color model based segmentation method
combined with template matching. There are 4 main process in this research. First, motion detection is used to
minimize the size of the image by subtracting image n with image n+m. Then, by using YCbCr color model based
segmentation, the image is separated by skin color area and non-skin color area. Third, is to reduce the noise by
using the blurring way and by filtering its wide. The last one is matching the area that last with template that has
been prepared to detect which area is face. The result of the research, from 217 images and 10 videos , shows
that this method reach up to 70,5 face detection accuration procentage. Platform: |
Size: 649216 |
Author:salman |
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Search - face detection using template matching