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人脸检测程序。在菜单上有许多功能选项,可实现多角度,多目的检测。-face detection procedures. In the menu options are many functions that can be achieved from different angles, multi-purpose testing.
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中科院的多视角人脸识别
Real-Time Multi-View Face Detection
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基于openCV的多角度人脸检测,融合了正脸侧脸haar分类器,具有极强鲁棒性-, The integration of multi-angle face detection based on openCV positive face side faces haar classifier, with strong robustness
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face detection
Face detection can be regarded as a more general case of face localization In face localization, the task is to find the locations and sizes of a known number of faces (usually one). In face detection, one does not have this addition
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基于Haar特征的多特征快速人脸检测,基于Haar特征的多特征快速人脸检测.-Haar based on the characteristics of fast multi-feature Face Detection, Haar-based features of the characteristics of the multi-face detection rapidly.
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本光盘共包括三个工程,分别是用于实现数字图像基本处理算法的DimageProcess工程,
用于实现图像融合的PixelFusion工程和用于人脸识别的FaceDetection工程。
关于程序的运行,
DImageProcess工程只需载入Bmp格式的文件,便可通过菜单实现各种处理算法,
需要强调一点,其只对256色格式的图片进行处理。
PixelFusion工程程序运行时,用户须载入两幅图片,其中全色图像选择给定的图片spot.bmp,
而多光谱图片则为给定的图片tm
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都是用matlab写的,复制到txt上了
(1)基于简单背景的人脸监测,针对视频,效果还不错,传的是txt,大家新建一个M文件,复制,然后把视频名与程序中的改成一致就可以了。
(2)对多椭圆的检测,非实际图像,无噪声,就是简单的椭圆,使用同上。-Are written with matlab, copy to the txt on the (1) human face based on a simple background monitoring, for video, the resu
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FaceDetectionBasedon Multi-BlockLBP Representation.本人在中科院搞人脸识别。上传必看的人脸检测论文-FloatBoost Learning and Statisitical Face Detection.pdf
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人脸检测,多实例,取多个实例来提取特征,形成一个特征池,分类器仍然是用级联生成,检测效果好,准确率比较高。-Face detection, multi-instance, take multiple instances to extract features, to form a feature pool with cascading classifier is still generating, testing effective, relatively high accuracy.
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提出了一种基于肤色的精确人脸定位算法,详细叙述了在图片的颜色调整与肤色检测,肤色区域的平滑、
分割与填充,候选眼睛的选取及配对中遇到的具体问题并提出了解决方案. 本算法能较为准确地定位彩色图像
中的正面、小角度偏侧和旋转的人脸,还能检测出一幅图中的多个人脸.-Presents a human face based on skin color precision positioning algorithm, described in detail in the image color ad
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haar小波处理 分类器 人脸检测 多级分类器-haar wavelet processing of face detection classifier multi-classifier
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人脸检测的研究具有重要的学术价值,人脸是一类具有相当复杂的细节变化的自然结构目标,对此类目标的挑战性在于:人脸由于外貌、表情、肤色等不同,具有模式的可变性;一般意义下的人脸上,可能存在眼镜、胡须等附属物;作为三维物体的人脸影像不可避免地受由光照产生的阴影的影响。因此,如果能够找到解决这些问题的方法,成功地构造出人脸检测系统,将为解决其他类似的复杂模式的检测问题提供重要的启示。-Face detection can be regarded as a specific case of object-
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基于多关联模板匹配的人脸检测.pdf,从网上付费得到的资料,值得学习。-Associated with template matching based on multi-face detection. Pdf, payment information obtained from the Internet, it is worth learning.
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基于多关联模板匹配的人脸检测.pdf,从网上付费得到的资料,值得学习。-Associated with template matching based on multi-face detection. Pdf, payment information obtained from the Internet, it is worth learning.
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从原始彩色图像中提取多阈值器官梯度图、双阈值肤色图、梯度方向图和灰度特征图等四种特征图像,并运用多姿态
知识模型和多姿态模板,实现了一种快速人脸检测算法
-Extracted from the original color image gradient map organ multi-threshold, dual-threshold color map and gray gradient patterns and other characteristics of the four
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复杂背景下多视角人脸检测与识别仿真需要的工具箱详解。-Complex Background Multi-View Face Detection and Recognition Detailed simulation toolbox needs.
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Multi-view face Detection
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提出了一种针对复杂环境下的过人脸检测方法,首先在CbCgCr空间利用直接最小二乘法构建了对光照和复杂背景鲁棒性更好肤色聚类模型,实现了准确的肤色检测;然后针对人脸中姿态和表情变化,提出了基于Adaboost的多姿态人脸检测,精确的实现了人脸检测定位。-Extraordinary face detection method for complex environments, the first space CbCgCr direct least squares meth
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人脸的检测与定位的程序实例,有界面,多方法,可以定位嘴巴眼睛头发。-
Instance of face detection and location, interface, multi-method, you can locate the mouth eyes hair.
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dataset of multi-lingual fonts
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