display_video

SURF 图像特征点快速提取法还有描述，可用于迅速匹配两张图片中的特征点(SURF image feature points extraction method also described fast, can be used to quickly match the image feature points in the two)

该源码为目标检测和跟踪算法 包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (The source code for target detection and tracking algorithm include: 1 Static background background prediction target detection 2 Static background frame difference method for target detection 3. Mean Shift tracking method 4 multi-target tracking methods focus)

利用opencv库写的一个关于图像孔洞填补的小程序，附加了效果图片(Using the opencv library to write a small program on the filling of the hole, the additional effect of the picture)

图像分割，完整程序，验证可行。新手上传，望支持。(image direct)

卡尔曼滤波是一种数据处理方法，它是一种线性最小方差无偏估计准则，基于系统 状态估计和当前观测，通过引入状态空间而获得的新的状态估计.本篇论文陈述了卡尔曼滤 波的基本思路和算法；并通过仿真，显示卡尔曼滤波的功能，以及如何用它来跟踪方向确定、速度恒定的飞行器。 (Kalman filter is a data processing method, which is a linear minimum variance unbiased estimation criteria, based on system state estimation and the current observations, obtained by introducing the state space of the new state estimate of the Kalman filter thesis statement the basic ideas and algorithms and through simulation, shows Kalman filtering functions, and how to use it to keep track of the direction determined constant speed aircraft.)

过特定人语音情感数据库的建立；语音情感特征提取；语音情感分类器的设计，完成了一个特定人语音情感识别的初步系统。对于单个特定人，可以识别平静、悲伤、愤怒、惊讶、高兴5种情感，除愤怒和高兴之间混淆程度相对较大之外，各类之间区分特性良好，平均分类正确率为93.7 。对于三个特定人组成的特定人群，可以识别平静、愤怒、悲伤3种情感，各类之间区分特性良好，平均分类正确率为94.4 。其中分类器采用混合高斯分布模型。(The system of speech emotion recognition)

检测视频中的运动目标以及阴影，并消除阴影，基于opencv，将RGB颜色空间根据一定的转换关系转换到HSV空间，最后消除阴影， 可以在vc6.0和vs2008上正常运行(Shadow detection algorithm based on HSV color space)

图像分割处理的小波变换算法源代码，使用vc++(Wavelet transform image segmentation algorithm source code vc++)

标记分水岭比较了开闭和基于重构的开闭的效果及分割染色后的效果图... 标记分水岭分割算法(Mark a watershed in comparing the opening and closing and effect diagram based on the effect of opening and closing and split reconstructed stained ... marked watershed segmentation algorithm)

采集RGB-D深度图像生成点云矩阵，属于RGB-D SLAM的前端处理过程(Collecting depth image to generate point cloud)