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Struck跟踪算法：Structed Output Tracking with Kernels (ICCV /2011年)
原理： Adaptive tracking-by-detection methods
最近做项目，需要借鉴一下这个算法，于是就打算好好学习这个算法。
算法下载地址：http://download.csdn.net/detail/sunboyiris/7681943
首先介绍一下如何调通这个算法，首先要引入两个库：Eigen库和OpenCV库
Eigen库配置：
Eigen库下载地址：http://eigen.tuxfamily.org/index.php?title=Main_Page#Download
解压后对VS操作如下：
然后调用其库函数就OK了。
OpenCV库配置：
见前面文章
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要看struct跟踪算法的效果，首先要看的是config.txt文件
# quiet mode disables all visual output (for experiments). quietMode = 0 # debug mode enables additional drawing and visualization. debugMode = 1 # base path for video sequences. sequenceBasePath = sequences //路径 # path for output results file. # comment this out to disable output. #resultsPath = log.txt # video sequence to run the tracker on. # comment this out to use webcam. #sequenceName = girl sequenceName = girl //调用算法提供的图像序列 # frame size for use during tracking. # the input image will be scaled to this size. frameWidth = 320 frameHeight = 240 # seed for random number generator. seed = 0 # tracker search radius in pixels. searchRadius = 30 # SVM regularization parameter. svmC = 100.0 # SVM budget size (0 = no budget). svmBudgetSize = 100 # image features to use. # format is: feature kernel [kernel-params] # where: # feature = haar/raw/histogram # kernel = gaussian/linear/intersection/chi2 # for kernel=gaussian, kernel-params is sigma # multiple features can be specified and will be combined feature = haar gaussian 0.2 //haar gaussian系数设置 #feature = raw gaussian 0.1 #feature = histogram intersection
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原文地址：http://blog.csdn.net/sunboyiris/article/details/38150411
