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边沿检测与提取轮廓跟踪的图象算法
边沿检测与提取轮廓跟踪，来自于源码中国 www.Cn700.com(edge detection and extraction of contour tracking, source from China www.Cn700.com)
- 2005-05-30 08:07:38下载
- 积分：1
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function SPFRC
说明： 根据粒径尺寸和数量生成随机骨料，添加钢纤维及聚丙烯纤维(Generate random aggregate)
- 2020-07-02 10:00:01下载
- 积分：1
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3DMM
说明： 3DMM模型是三维人脸重建的基础模型，用于三维人脸重建任务。(3dmm model is the basic model of 3D face reconstruction, which is used for 3D face reconstruction task.)
- 2021-03-16 16:49:21下载
- 积分：1
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FaceDetectorOtherversion
人脸检测的一个程序,adaboost+cascade+haar
能运行(Face detection of a program, adaboost+ Cascade+ Haar to run)
- 2008-12-16 15:50:47下载
- 积分：1
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Satellite-orbit
本代码用于模拟卫星星下点在地球表面上的投影。可以在程序中给定六要素及其他相关参数，就可以利用MATLAB呈现出仿真图。(The code for a simulated satellite point on the Earth' s surface projection. May be given in the program six elements and other relevant parameters, you can use MATLAB simulation showing a map.)
- 2016-10-10 17:01:51下载
- 积分：1
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Harris-Matlab-1
Code Harris corner detector matlab 1
- 2011-04-30 00:07:50下载
- 积分：1
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TEMP
关系JPEG在matlab中的一些应用，给大家使用(JPEG relations in matlab some applications, to the use of U.S.)
- 2008-03-26 13:55:04下载
- 积分：1
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improve_LBF
水平集最新算法，基于局部能量函数，并做了改进(level set new Algorithm, make some improve)
- 2009-11-10 10:29:00下载
- 积分：1
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OTSU2Dmy
说明： 灰度图像分割，二维大津法或二维最大类间方差法(2D Maximum Between Cluster Variance)
- 2010-04-01 09:09:35下载
- 积分：1
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IET_CV_SOAMST_2011
一个比例和方向自适应均值漂移跟踪算法（SOAMST）
提出本文所要解决的问题，如何估计的规模和方向
改变均值漂移下的目标跟踪框架。在原来的均值偏移
跟踪算法，可以很好地估计目标的位置，规模的同时，
方向的变化，不能自适应估计。考虑到图像（重量）
是来自于目标运动模型和候选模型可以代表的可能性，一个
像素属于目标，我们证明了原来的均值漂移跟踪算法可以
推导出的重量图像的零阶和一阶矩。随着零阶
矩和目标模型和候选模型之间的Bhattacharyya系数，
提出了简单而有效的方法来估计的规模为目标。然后一种方法，
利用估计的区域和第二阶中心矩，提出
自适应地估计目标的宽度，高度和方向的变化。广泛
实验来证实所提出的方法，并验证其可靠性
规模和方向变化的目标。(A scale and orientation adaptive mean shift tracking (SOAMST) algorithm is
proposed in this paper to address the problem of how to estimate the scale and orientation
changes of the target under the mean shift tracking framework. In the original mean shift
tracking algorithm, the position of the target can be well estimated, while the scale and
orientation changes can not be adaptively estimated. Considering that the weight image
derived from the target model and the candidate model can represent the possibility that a
pixel belongs to the target, we show that the original mean shift tracking algorithm can be
derived using the zeroth and the first order moments of the weight image. With the zeroth order
moment and the Bhattacharyya coefficient between the target model and candidate model, a
simple and effective method is proposed to estimate the scale of target. Then an approach,
which utilizes the estimated area and the second order center moment, is proposed to
adaptively e)
- 2013-08-06 16:55:36下载
- 积分：1
