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

Struck跟踪算法（一）