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Description: 基于OPENCV的静止图像的HOG特征提取算法的全部程序，完全可用于各种图像的HOG特征提取，以进一步训练分类器进行行人检测-source code that apply to the pedestrian detection based on OPENCV.this document can help you extract HOG features from any type image which include human in it
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Size: 4096 |
Author: lightblueboy |
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Description: HoG matlab，内含HOG算法基本代码-HoG matlab code
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Size: 3072 |
Author: 杨策 |
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Description: HOG的详细介绍和源代码，以及附带详细PPT介绍，对学习HOG很有帮助-HOG detailed description and source code, and the PPT with detailed description, very helpful in learning HOG
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Author: mattew |
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Description: HOG特征的实现方案，用于人脸识别，已经被opencv采用-the feature of HOG
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Size: 518144 |
Author: Clarence |
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Description: cvpr07年 对象检测代码 hog+svm，压缩包里含有行人，车辆等分类器，可以直接检测-cvpr07 on object identification code hog+ svm, compression bag with pedestrians, vehicles and other classifiers
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Size: 5592064 |
Author: liurui |
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Description: 该程序分别提取正负样本图像的HOG和LBP特征，利用支持向量机进行样本训练，得到行人分类器。利用训练好的分类器进行检测，实验结果表明，该方法可以有效检测出图像中的行人，并达到了较好的检测结果。-A novel approach based on combining Histogram of oriented gradients (HOG) and LocalBinary Pattern(LBP) is suggested in the program.Also liner SVM is acted as the classifier,and the experiment suggests that the method can better deal with human detection.
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Size: 14336 |
Author: 邵文 |
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Description: 一种基于HOG-LBP特征的人脸检测方法，对于遮挡的人体非常有效。-By combining Histograms of Oriented Gradients (HOG)
and Local Binary Pattern (LBP) as the feature set, we pro-
pose a novel human detection approach capable of handling
partial occlusion. Two kinds of detectors, i.e., global de-
tector for whole scanning windows and part detectors for
local regions, are learned from the training data using lin-
ear SVM. For each ambiguous scanning window, we con-
struct an occlusion likelihood map by using the response
of each block of the HOG feature to the global detector.
The occlusion likelihood map is then segmented by Mean-
shift approach. The segmented portion of the window with
a majority of negative response is inferred as an occluded
region. If partial occlusion is indicated with high likelihood
in a certain scanning window, part detectors are applied
on the unoccluded regions to achieve the fi nal classifi ca-
tion on the current scanning window. With the help of the
augmented HOG-LBP feature and the global-part occ
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Size: 3078144 |
Author: 有来有去 |
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Description: matlab 实现的hog和lbp 结合的行人检测-matlab hog-lbp detection
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Size: 13312 |
Author: zxc |
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Description: HOG-LBP+detection 行人检测-HOG-LBP+detection Pedestrian Detection
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Size: 14336 |
Author: 朱涛 |
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Description: 基于HOG+LBP+HIKSVM的行人检测算法matlab代码实现，里面包含了libsvm-mat-3.0-1软件包.-the algorithm implementation
of pedestrian detection based on the dates+ LBP+ HIKSVM，it contains the libsvm-mat-3.0-1 package
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Size: 47104 |
Author: xiaoyufei |
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Description: HOG_LBP is method to detect pedestrians image
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Size: 955392 |
Author: Clopezriv |
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Description: Hog + LBP + svm 行人检测-Hog+ LBP+ svm pedestrian detection
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Size: 58368 |
Author: tony |
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Description: 为了实现复杂环境下的人脸特征有效表达，提出一种改进的梯度方向直方图（ＨＯＧ）人脸识别方法．首先以人脸图像网格作为采样窗口并在其上提取 ＨＯＧ特征；然后将所有网格 ＨＯＧ特征向量进行组合，实现整个人脸特
征表达；最后采用最近邻分类器进行识别．另外，比较了该方法与Ｇａｂｏｒ小波和局部二值模式（ＬＢＰ）２种著名的人脸
局部特征表示方法的优劣．实验结果表明，在调优的 ＨＯＧ参数下，在具有光照和时间环境等复杂变化的ＦＥＲＥＴ人
脸库中，较少维数的 ＨＯＧ特征比ＬＢＰ特征有更好的表现，而且 ＨＯＧ特征提取时间和特征向量维数比Ｇａｂｏｒ小波方法更具有优势-In order to achieve facial features in complex environments valid expression, an improved gradient direction histogram (HOG) face recognition method. Firstly face image and extract the grid as a sample window HOG features on it then all mesh HOG feature vector combination, realize the whole people express facial feature Finally, nearest neighbor classifier to identify. In addition, the comparison of the method with Gabor wavelet and local binary pattern (LBP) 2 famous facial features indicate the quality of the local approach. Experimental results show that HOG parameter tuning in FERET face with complex changes in the environment of light and time, the characteristic dimension of less than HOG LBP features better performance, and feature extraction time and HOG dimension of feature vectors have an advantage over Gabor wavelet method
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Size: 1274880 |
Author: wang |
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Description: 特征提取的工具包，实现各种特征，如hog,lbp,sift.-Feature extraction kit achieve a variety of features, such as hog, lbp, sift.
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Size: 18255872 |
Author: 刘晓晶 |
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Description: 行人检测中的HoG和HoG-LBP算法的对比试验。-Pedestrian Detection comparative test HoG and HoG-LBP algorithm.
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Size: 11264 |
Author: Bao Donghai |
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Description: 本方法是hog+lbp+svm来判断是否为行人，函数库为opencv，代码为C++，hog是opencv自带的，lbp为均匀模式，59维度，训练样本为INRIA数据集-opencv lbp svm president detection inria data
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Author: 陶峰 |
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Description: Building Detection Using Enhanced HOG-LBP
features and Region Refinement Processes
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Size: 1858560 |
Author: mingjun wang |
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Description: 检测lbp+hog特征，MATLAB代码，用于特征识别和检测(Detect lbp+hog features)
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Size: 13312 |
Author: steve_ustc
|
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Description: 融合hog与lbp特征的图像分类，使用svm进行分类，最终给出运行混淆矩阵(The image classification of hog and LBP features is classified by SVM, and the run obfuscation matrix is finally given.)
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Size: 1024 |
Author: wmqqiu |
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Description: HOG LBP 在python matlab C++环境下的实现(Implementation of HOG LBP in Python matlab C++ environment)
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Size: 4008960 |
Author: kzlee |
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