To be better
Unpack it in your [PATH] and open it using Matlab. Add voc-release5 file to path in MATLAB. And you should read README in voc-release5 file firstly.
If you want to use this code, you first step is run compile.m. But voc-release5 code can only run on linux or OS X, So let’s modify source code in order to make it work on Windows.
统计学习，也称统计机器学习（statistical machine learning）。统计学习方法：监督学习（supervised learning）、非监督学习（unsupervised learning）、半监督学习（semi-supervised learning）、强化学习（reinforcement learning）等。
统计学习方法三要素：模型（model）、策略（strategy）、算法（algorithm）。
In this chapter, we will cover:
- Detecting image contours with the Canny operator
- Detecting lines in images with the Hough transform （使用Hough变换检测直线）
- Fitting a line to a set of points （用直线拟合一组点）
- Extracting the components’ contours（提取连通区域的轮廓）
- Computing components’ shape descriptors
主要是记录一些自己遇到的渲染Markdown不成功的案例以及解决方法，这里说的解析不成功是在其他的Markdown渲染器下可以渲染成功的，但是在hexo下不能渲染成功。或者写的latex代码明明在其他渲染器可以成功渲染，但是在hexo下就不行，我又不太懂这些，所以觉得实在是太诡异。
- Introduction
- Method
- 动态系统的状态空间模型
- Bayes 滤波理论
- 重要性采样
- SIS算法
- SIR算法
- Resample算法
- Result&Discussion
- References
In this chapter, we will cover:
- Filtering images using low-pass filters
- Filtering images using a median filter
- Applying directional filters to detect edges
- Computing the Laplacian of an image
In this chapter, we will cover:
- Eroding and dilating images using morphological filters
- Opening and closing images using morphological filters
- Detecting edges and corners using morphological filters
- Segmenting images using watersheds
- Extracting foreground objects with the GrabCut algorithm
In this chapter, we will cover:
- Computing the image histogram(计算图像的直方图)
- Applying look-up tables to modify image appearance(使用查找表修改图像外观)
- Equalizing the image histogram(直方图均衡化)
- Backprojecting a histogram to detect specific image content(反向投影直方图去检测特定的图像内容)
- Using the mean shift algorithm to find an object(使用均值漂移算法去寻找物体)
- Retrieving similar images using histogram comparison(比较直方图来检索相似图像)
In this chapter, we will cover:
- City block distance and Euclidean distance(街区距离和欧式距离)
- Using the Singleton design pattern(单例模式)
- Converting color spaces(颜色空间转换)
本节导读：
- Writing effcient image scanning loops(编写高效的图像遍历循环)
- Scanning an image with neighbor access(遍历图像和邻域操作)
- Performing simple image arithmetic
- Defining regions of interest