搜索资源列表
CKPCA-HOG-SVM
- 为了准确地对监控场景中的运动目标进行语义上的分类，提出了一种基于聚类的核主成分分析梯度方向直方图和二又决策树支持向量机的运动目标分类算法。-In order to accurately monitor the movement of scene targets semantic classification, the clustering based on kernel principal component analysis of gradient direction histograms,
hog
- Hog try I try to implement hog descr iptor
CODE
- 1.GeometricContext文件是完成图片中几何方向目标分类。 参考文献《Automatic Photo Pop-up》Hoiem 2005 2 GrabCut文件是完成图像中目标交互式分割 参考文献《“GrabCut” — Interactive Foreground Extraction using Iterated Graph Cuts》 C. Rother 2004 3 HOG文件是自己编写的根据HOG特征检测行人的matlab代码 4 虹膜识别程序
exercise5
- Matlab HOG exercise matlab svm learning
pedestrain
- 经典的行人检测算法，利用HOG和SVM实现此算法。已调试可以正常运行。-Classic pedestrian detection algorithm, HOG and SVM to implement this algorithm. Has debugging normal operation.
Histogram-OrientedGradient
- HOG（Histogram of Oriented Gradient）方向梯度直方图，主要用来提取图像特征，最常用的是结合svm进行行人检测。-HOG (Histogram of Oriented Gradient) direction of the gradient histogram is mainly used to extract image features, the most commonly used is a combination of svm detect pedestria
HOG_LBP
- 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.)
da
- 基于码本（codebook）的背景建模的背景差分法+级联基于LBK或haar的adaboost和基于hog的svm分类器+快速hough圆变换进行人头识别+基于区域特征的目标跟踪算法。(编程) AdaBoost是一种增强性机器学习算法，它用于把弱分类器联合成强分类器；SVM本身就是(Background modeling based on codebook (codebook) background difference method + cascade based on LBK or Haa
fa(4)
- 基于码本（codebook）的背景建模的背景差分法+级联基于LBK或haar的adaboost和基于hog的svm分类器+快速hough圆变换进行人头识别+基于区域特征的目标跟踪算法。(编程)(Background modeling based on codebook (codebook) background difference method + cascade based on LBK or Haar AdaBoost and hog based SVM Classifier + fast
gmm(2)
- 基于码本（codebook）的背景建模的背景差分法+级联基于LBK或haar的adaboost和基于hog的svm分类器+快速hough圆变换进行人头识别(Background modeling based on codebook (codebook) background difference method + cascade based on LBK or Haar AdaBoost and hog based SVM Classifier + fast Hough circle trans
rq(3)
- 基于码本（codebook）的背景建模的背景差分法+级联基于LBK或haar的adaboost和基于hog的svm分类器+快速hough圆变换进行人头识别+基于区域特征的目标跟踪算法。(编程) AdaBoost是一种增强性机器学习算法，它用于把弱分类器联合成强分类分类器(Background modeling based on codebook (codebook) background difference method + cascade based on LBK or Haar AdaB
HOGSVM
- 输入训练样本集和测试样本集，通过提取HOG然后用SVM实现分类。(Input training samples and test samples, extract HOG and implement classification with SVM.)