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: 用SVM实现红外人体检测,主要方法是聚类分析-Using SVM for infrared human body detection, mainly by cluster analysis Platform: |
Size: 8206336 |
Author:yinlili |
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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. Platform: |
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 Platform: |
Size: 3078144 |
Author:有来有去 |
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