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针对人脸识别中图像前期处理的人脸图像归一化问题,用AdaBoost Cascade方法检测出人脸和眼裂,提出以两眼裂中心点连线为基准进行水平旋转和尺度的归一化矫正方法。与通常的利用两眼瞳距方法相比较,该方法更加快速准确,能处理多达20°的倾斜,对戴眼镜、图像模糊、俯视、仰视、斜视等情况的鲁棒性更好。
A novel approach was presented, using the line between the two center points of the palpebral fiss
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基于ADABOOST的人脸检测代码,使用继承的策略,包括特征的计算,提取,ADABOOST训练,级联,最后训练出数据,还有注释,可以帮助大家研究ADBOOST-Based on ADABOOST face detection code, the use of inheritance strategies, including the calculation of features, extraction, ADABOOST training cascade, the last train out
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基于Adaboost级联分类的人脸和人眼检测,其中的三个xml是Adaboost分类器参数-Adaboost cascade based on the human face and eye detection, three of which are Adaboost classifier parameters xml
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人脸检测的一个程序,adaboost+cascade+haar
能运行-Face detection of a program, adaboost+ Cascade+ Haar to run
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基于adaboost的构造的cascade用于快速检测人脸,能够实时检测视频中的人脸。没有采用opencv的代码。-Adaboost based on the structure of the cascade for the rapid detection of human faces, real-time video can face. Did not use the code opencv.
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这片论文描述了动态物体的特征跟踪,用到了15个框架。拥有很强的适应性和跟踪能力。作为人脸识别,模式识别,动态跟踪的开发人员,有很好的参考价值。用c++编写,如果用OpenCV更好-This paper describes a visual object detection framework that is capable of processing
images extremely rapidly while achieving high detection rates. There ar
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训练好的人脸分类器,可直接载入运行,基于adaboost的级联分类器-Trained face classifier, can be directly loaded to run, based on cascade classifier adaboost
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基于adaboost的构造的cascade用于快速检测人人脸,能够实时检测视频中的人脸。没有采用opencv的代码。
-Based on the cascade of adaboost constructed for rapid detection of all face, real-time detection of the face in the video. Of opencv code.
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一种机器视觉的物体检测算法,是一种先进物体检测算法,全英文描述.讲述一种机器视觉的物体检测算法的实现-his paper describes a visual object detection framework that is capable of processing images extremely
rapidly while achieving high detection rates. There are three key contributions. The fi r
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this codes is Source code for face detection of viola paper.of its Features is:
Feature Computation: The “Integral” image representation
Feature Selection: The AdaBoost training algorithm .
Real-timeliness: A cascade of classifiers.-this code
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基于AdaBoost和Cascade算法的人脸检测-Face detection based on AdaBoost and Cascade algorithm
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基于dsp的人脸识别,使用harr特征和adaboost级联分类器(Based on dsp face recognition, use the harr feature and the adaboost cascade classifier)
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人脸检测:
第一部分,使用Harr-like特征表示人脸,使用“ 积分图”实现特征数值的快速计算;
第二部分, 使用Adaboost算法挑选出一些最能代表人脸的矩形特征( 弱分类器),按照加权投票的方式将弱分类器构造为一个强分类器;
第三部分, 将训练得到的若干强分类器串联组成一个级联结构的层叠分类器,级联结构能有效地提高分类器的检测速度。(Face detection:
In the first part, the Harr-like feature is used t
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