jianguo_wang

摘要： ACCEPTED CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION 2001Rapid Object Detection using a Boosted Cascade of SimpleFeatures简单特征的优化级联在快速目标检测中的应用Paul Viola Michael Jonesviola@merl.com mjones@crl.dec.comMitsubishi Electric Research Labs Compaq CRL ... 阅读全文

摘要： _stscanf_s (sscanf)正则表达式{%[*] [width] [{h | l | I64 | L}]type | ' ' | '\t' | '\n' | 非%符号}，注：{a|b|c}表示a,b,c中选一，[d],表示可以有d也可以没有d。width:宽度，一般可以忽略，用法如：const char sourceStr[] = "hello, world";char buf[10] = {0};sscanf(sourceStr, "%5s", buf); //%5s，只取5个字符cout &l 阅读全文

摘要： 1名称编辑函数原型:int sscanf(constchar*, const char *, ...);int sscanf(const char *buffer,const char *format,[argument ]...);buffer存储的数据format格式控制字符串argument 选择性设定字符串sscanf会从buffer里读进数据，依照format的格式将数据写入到argument里。2头文件编辑#include3返回值编辑成功则返回参数数目，失败则返回-1，错误原因存于errno中。4说明编辑sscanf与scanf类似，都是用于输入的，只是后者以键盘(stdin)为输 阅读全文

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摘要： VS多行注释快捷键注释：Ctrl+K,Ctrl+C取消注释：Ctrl+K,Ctrl+U 阅读全文

摘要： Matlab函数kmeansK-means聚类算法采用的是将N*P的矩阵X划分为K个类，使得类内对象之间的距离最大,而类之间的距离最小。使用方法：Idx=Kmeans(X,K)[Idx,C]=Kmeans(X,K)[Idx,C,sumD]=Kmeans(X,K)[Idx,C,sumD,D]=Kmeans(X,K)[…]=Kmeans(…,’Param1’,Val1,’Param2’,Val2,…)各输入输出参数介绍：X N*P的数据矩阵K 表示将X划分为几类，为整数Idx N*1的向量，存储的是每个点的聚类标号C K*P的矩阵，存储的是K个聚类质心位置sumD 1*K的和向量，存储的是类间所有 阅读全文

摘要： MATLAB中floor、round、ceil、fix区别B = floor(A) rounds the elements of A to the nearest integers less than or equal to A. For complex A, the imaginary and real parts are rounded independently. (floor：朝负无穷方向舍入)B = ceil(A) rounds the elements of A to the nearest integers greater than or equal to A. For com. 阅读全文

摘要： IntroductionThe problem of searching for patterns in data is a fundamental one and has a long and successful history. For instance, the extensive astronomical observations of Tycho Brahe in the 16th century allowed Johannes Kepler to discover the empirical laws of planetary motion, which in turn pro 阅读全文

摘要： PrefacePattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years. In particular, Bayesian methods 阅读全文

摘要： 1.介绍HOG（Histogram of Oriented Gradient）是2005年CVPR会议上，法国国家计算机科学及自动控制研究所的Dalal等人提出的一种解决人体目标检测的图像描述子，该方法使用梯度方向直方图（Histogram of Oriented Gradients,简称HOG）特征来表达人体，提取人体的外形信息和运动信息，形成丰富的特征集。2.生成过程1）图像归一化归一化图像的主要目的是提高检测器对光照的鲁棒性，因为实际的人体目标可能出现的各种不同的场合，检测器，必须对光照不太敏感才会有好的效果。2)利用一阶微分计算图像梯度图像平滑对于灰度图像，一般为了去除噪点，所以会先利 阅读全文