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文件名称:houghForest

  • 所属分类：
    Special Effects
  • 标签属性：
    [Matlab] [源码]
  • 上传时间：
    2012-10-27
  • 文件大小：
    5.27mb
  • 已下载：
    0次
  • 提 供 者：
    Joann*****
  • 相关连接：
    无
  • 下载说明：
    别用迅雷下载，失败请重下，重下不扣分！
修正介绍说明

介绍说明－－下载内容来自于网络，使用问题请自行百度

这个是Dr. Juergan Gall写的检测识别图片中的物体，有关的文章名字是Class-specific Hough Forests for Object detection. hough森林方法结合了随机森林和Hough选票去估计物体中心的可能。-A method for the detection of instances of an object class.A class-specific Hough forest is a random forest that maps image patch appearance to the probabilistic vote about the possible location of the object centroid
(系统自动生成,下载前可以参看下载内容)

下载文件列表

65/
65/CRForest-Detector.cpp
65/CRForest.h
65/CRForestDetector.cpp
65/CRForestDetector.h
65/CRPatch.cpp
65/CRPatch.h
65/CRTree.cpp
65/CRTree.h
65/example/
65/example/config.txt
65/example/datasets/
65/example/datasets/dataset.txt
65/example/datasets/INRIA/
65/example/datasets/INRIA/results/
65/example/datasets/INRIA/results/compareDET.m
65/example/datasets/INRIA/results/histsmooth.txt
65/example/datasets/INRIA/results/OLTbinaries/
65/example/datasets/INRIA/results/OLTbinaries/HOG/
65/example/datasets/INRIA/results/OLTbinaries/HOG/WindowTest_Negative/
65/example/datasets/INRIA/results/OLTbinaries/HOG/WindowTest_Negative/histogram.txt
65/example/datasets/INRIA/results/OLTbinaries/HOG/WindowTest_Positive/
65/example/datasets/INRIA/results/OLTbinaries/HOG/WindowTest_Positive/histogram.txt
65/example/datasets/INRIA/results/plotDET.m
65/example/datasets/INRIA/results/plotHOG.m
65/example/datasets/INRIA/results/schistsmooth.txt
65/example/datasets/TUD/
65/example/datasets/TUD/results/
65/example/datasets/TUD/results/4DISM-train210_roc.mat
65/example/datasets/TUD/results/Art-ISM-train400_roc.mat
65/example/datasets/TUD/results/HOG_roc.mat
65/example/datasets/TUD/results/roc2.mat
65/example/datasets/TUD/results/roc_mr.mat
65/example/datasets/TUD/results/tudROC.m
65/example/datasets/TUD/trees/
65/example/datasets/TUD/trees/config.txt
65/example/datasets/TUD/trees/treetable000.txt
65/example/datasets/TUD/trees/treetable001.txt
65/example/datasets/TUD/trees/treetable002.txt
65/example/datasets/TUD/trees/treetable003.txt
65/example/datasets/TUD/trees/treetable004.txt
65/example/datasets/TUD/trees/treetable005.txt
65/example/datasets/TUD/trees/treetable006.txt
65/example/datasets/TUD/trees/treetable007.txt
65/example/datasets/TUD/trees/treetable008.txt
65/example/datasets/TUD/trees/treetable009.txt
65/example/datasets/TUD/trees/treetable010.txt
65/example/datasets/TUD/trees/treetable011.txt
65/example/datasets/TUD/trees/treetable012.txt
65/example/datasets/TUD/trees/treetable013.txt
65/example/datasets/TUD/trees/treetable014.txt
65/example/datasets/WeizmannHorse/
65/example/datasets/WeizmannHorse/results/
65/example/datasets/WeizmannHorse/results/horseROC.m
65/example/datasets/WeizmannHorse/results/roc_mr.mat
65/example/datasets/WeizmannHorse/results/roc_sc2_a.mat
65/example/datasets/WeizmannHorse/results/roc_sc2_b.mat
65/example/datasets/WeizmannHorse/trees/
65/example/datasets/WeizmannHorse/trees/config.txt
65/example/datasets/WeizmannHorse/trees/treetable000.txt
65/example/datasets/WeizmannHorse/trees/treetable001.txt
65/example/datasets/WeizmannHorse/trees/treetable002.txt
65/example/datasets/WeizmannHorse/trees/treetable003.txt
65/example/datasets/WeizmannHorse/trees/treetable004.txt
65/example/datasets/WeizmannHorse/trees/treetable005.txt
65/example/datasets/WeizmannHorse/trees/treetable006.txt
65/example/datasets/WeizmannHorse/trees/treetable007.txt
65/example/datasets/WeizmannHorse/trees/treetable008.txt
65/example/datasets/WeizmannHorse/trees/treetable009.txt
65/example/datasets/WeizmannHorse/trees/treetable010.txt
65/example/datasets/WeizmannHorse/trees/treetable011.txt
65/example/datasets/WeizmannHorse/trees/treetable012.txt
65/example/datasets/WeizmannHorse/trees/treetable013.txt
65/example/datasets/WeizmannHorse/trees/treetable014.txt
65/example/detect/
65/example/detect/detect-0_sc0_c0.png
65/example/detect/detect-0_sc1_c0.png
65/example/detect/detect-0_sc2_c0.png
65/example/detect/detect-10_sc0_c0.png
65/example/detect/detect-10_sc1_c0.png
65/example/detect/detect-10_sc2_c0.png
65/example/detect/detect-11_sc0_c0.png
65/example/detect/detect-11_sc1_c0.png
65/example/detect/detect-11_sc2_c0.png
65/example/detect/detect-12_sc0_c0.png
65/example/detect/detect-12_sc1_c0.png
65/example/detect/detect-12_sc2_c0.png
65/example/detect/detect-13_sc0_c0.png
65/example/detect/detect-13_sc1_c0.png
65/example/detect/detect-13_sc2_c0.png
65/example/detect/detect-14_sc0_c0.png
65/example/detect/detect-14_sc1_c0.png
65/example/detect/detect-14_sc2_c0.png
65/example/detect/detect-15_sc0_c0.png
65/example/detect/detect-15_sc1_c0.png
65/example/detect/detect-15_sc2_c0.png
65/example/detect/detect-16_sc0_c0.png
65/example/detect/detect-16_sc1_c0.png
65/example/detect/detect-16_sc2_c0.png
65/example/detect/detect-17_sc0_c0.png
65/example/detect/detect-17_sc1_c0.png
65/example/detect/detect-17_sc2_c0.png
65/example/detect/detect-18_sc0_c0.png
65/example/detect/detect-18_sc1_c0.png
65/example/detect/detect-18_sc2_c0.png
65/example/detect/detect-1_sc0_c0.png
65/example/detect/detect-1_sc1_c0.png
65/example/detect/detect-1_sc2_c0.png
65/example/detect/detect-2_sc0_c0.png
65/example/detect/detect-2_sc1_c0.png
65/example/detect/detect-2_sc2_c0.png
65/example/detect/detect-3_sc0_c0.png
65/example/detect/detect-3_sc1_c0.png
65/example/detect/detect-3_sc2_c0.png
65/example/detect/detect-4_sc0_c0.png
65/example/detect/detect-4_sc1_c0.png
65/example/detect/detect-4_sc2_c0.png
65/example/detect/detect-5_sc0_c0.png
65/example/detect/detect-5_sc1_c0.png
65/example/detect/detect-5_sc2_c0.png
65/example/detect/detect-6_sc0_c0.png
65/example/detect/detect-6_sc1_c

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