Description: ChainCascade， harr 特征进行分类器训练，得到一个级联的boosted分类器，训练目标特征，检测物体，这是从opencv库 转化成 vc++源代码，有一位博士完成，很不错。-ChainCascade, Harr features classifier training to be a cascade boosted classifier, training objectives features, object detection, which is OpenCV library into vc source code, complete with a doctorate, is pretty good. Platform: |
Size: 323584 |
Author:陈其星 |
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Description: 用帧间差法及Adaboost算法实现人脸检测，可以增加人脸检测的效率-Using inter-frame difference method and the Adaboost face detection algorithm, it can increase the efficiency of face detection Platform: |
Size: 2004992 |
Author:萧枫 |
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Description: 利用级联的HAAR分类器寻找检测目标，采用OPENCV编写，代码简单运行稳定-Use the haar classifier cascade testing to find the target, using OPENCV preparation, code simple and stable operation Platform: |
Size: 183296 |
Author:鄢胜勇 |
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Description: 利用级联的Haar分类其寻找检测目标。核心函数cvHaarDetectObjects使用针对某目标物体的级联分类器在图像中找到包含目标物体的矩形区域，并将这些区域作为一系列的矩形框返回。-Haar cascade classification using its search for target detection. CvHaarDetectObjects core function for a target object using the cascade classifier found in the image of the rectangle that contains the object region, and these regions as a series of rectangular box to return. Platform: |
Size: 179200 |
Author:孔守斌 |
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Description: adaboost 弱分类器构成强分类器算法，并作图，分析样本数对性能的影响-constitute a weak classifier AdaBoost strong classifier algorithm, and mapping, analysis of sample size on the performance of Platform: |
Size: 9216 |
Author:毛楠 |
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Description: 利用级联的Haar分类器寻找检测目标，这是OPENCV上的程序，与大家分享-Using the Haar classifier cascade find Detected goals, OPENCV This is on the procedures to share with you Platform: |
Size: 178176 |
Author:田贵友 |
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Description: 图像处理中分类器级联处理的一些代码，可以将分类合并为一个XML文件-Image processing cascade classifier to deal with some of the code Platform: |
Size: 1024 |
Author:jackson |
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Description: 利用级联SVM的人体检测方法从图像中检测出人体是计算机视觉应用中的关键步骤。通过一个由简到繁的级联线性SVM分类器将级
联拒绝的机制与梯度方向直方图特征相结合,实现了一个准确和快速的人体检测器,整个检测器由级联的线性
SVM分类器组成。实验结果表明,在保持Dalal算法检测准确性的同时,大幅的提高了检测速度,每秒平均可以处
理12帧左右的320 ×240的图像。-Human detection using cascade SVM method detected from the images of computer vision applications, the human body is a key step. From the simple to the complex through a cascade of linear SVM classifier with the cascade mechanism of rejection combined histograms of oriented gradients to achieve an accurate and rapid detection of the human body, the detector by a cascade of linear SVM classifier component. The results show that the accuracy in maintaining Dalal algorithm to detect the same time, substantially increase the detection rate of 12 frames per second on average can process about 320 × 240 image. Platform: |
Size: 482304 |
Author:lilin |
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Description: 最经典AdaBoost实现，适合初学，有大量详细的注释，容易理解-This a classic AdaBoost implementation, in one single file with easy understandable code.
The function consist of two parts a simple weak classifier and a boosting part:
The weak classifier tries to find the best threshold in one of the data dimensions to separate the data into two classes-1 and 1
The boosting part calls the classifier iteratively, after every classification step it changes the weights of miss-classified examples. This creates a cascade of "weak classifiers" which behaves like a "strong classifier" 。 Platform: |
Size: 4096 |
Author:wj |
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Description: 基于haar特征的adaboost级联分类器的人脸识别应用，可直接运行-Adaboost cascade haar feature based classifier for face recognition applications can be run directly Platform: |
Size: 4583424 |
Author:苏军 |
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Description: 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 Platform: |
Size: 4944896 |
Author:苏军 |
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Description: 如何利用opencv训练自己的分类器，内有多篇资料，本人用过一次，可能样本太少，效果不太好-How-to build a cascade of boosted classifiers based on Haar-like features. Platform: |
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Author: |
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Description: 提出一种多尺度方向(multi-scale orientation,简称 MSO)特征描述子用于静态图片中的人体目标检
测.MSO 特征由随机采样的图像方块组成,包含了粗特征集合与精特征集合.其中,粗特征是图像块的方向,而精特征
由 Gabor 小波幅值响应竞争获得.对于两种特征,分别采用贪心算法进行选择,并使用级联 Adaboost 算法及 SVM 训
练检测模型.基于粗特征的 Adaboost 分类器能够保证高的检测速度,而基于精特征的 SVM 分类器则保证了检测精
度.另外,通过 MSO 特征块的平移,使得所提算法能够检测多视角的人体.通过对于 MSO 特征块的装配,使得算法能
够检测人群中相互遮挡的人体目标.在INRIA公共测试集合及SDL多视角测试集合上的实验结果表明,算法具有对视角与遮挡的鲁棒性和较高的检测速度. -The multi-scale orientation (MSO) features for pedestrian detection in still images are put forwarded in
this paper. Extracted on randomly sampled square image blocks (units), MSO features are made up of coarse and
fine features, which are calculated with a unit gradient and the Gabor wavelet magnitudes respectively. Greedy
methods are employed respectively to select the features. Furthermore, the selected features are inputted into a
cascade classifier with Adaboost and SVM for classification. In addition, the spatial location of MSO units can be
shifted, are used to the handle multi-view problem and assembled therefore, the occluded features are completed
with average features of training positives, given an occlusion model, which enable the proposed approach to work
in crowd scenes. Experimental results on INRIA testset and SDL multi-view testset report the state-of-arts results on
INRIA include it is 12.4 times the faster than SVM+HOG method. Platform: |
Size: 1868800 |
Author:尹世荣 |
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Description: 级联分类器检测人脸，并定位脸部、眼睛和嘴巴，用到OPENCV分类器-Cascade classifier detects the face, and the positioning of the face, eyes and mouth, used OPENCV classification Platform: |
Size: 2993152 |
Author:glemo |
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Search - cascade classifier