Description: 学习mean-shift均值偏移算法的好文章，可以参考参考的-learning mean-shift offset algorithm mean good articles, reference can refer to the Platform: |
Size: 2999296 |
Author:方锐 |
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Description: 可以得到图像的随机噪声、椒盐噪声、均值滤波、分布均衡、小波变换等等功能。-Images can be random noise, salt and pepper noise, mean filter, a balanced distribution, wavelet transform and so on. Platform: |
Size: 3996672 |
Author:依静 |
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Description: 开发工具采用VC++，用于均值滤波，能有效地去除噪声。-Development tools used VC++, For the mean filter can effectively remove the noise. Platform: |
Size: 481280 |
Author:富裕 |
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Description: 此程序是matlab中给出矩阵均值的程序，注释详尽，使用简单，其中的注释详细，自己可以对变量做相应的变换-This procedure is given in matlab matrix mean the procedures, the Notes detailed, easy to use, which notes in detail that they can make the corresponding change of variables Platform: |
Size: 1024 |
Author:gengxiang |
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Description: this mean shift one of image processing famous segmentation techniques, it is programmed in matlab-this is mean shift one of image processing famous segmentation techniques, it is programmed in matlab Platform: |
Size: 2048 |
Author:me |
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Description: 基于均值漂移算法实现图像的分割，总共带有三个文件，其中两个是两个子程序-Based on mean-shift image segmentation algorithm, with a total of three documents, two of which are the two subroutines Platform: |
Size: 2048 |
Author:hahadinghaha |
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Description: 用Matlab实现基于均值平移（meanshift)算法的灰度图像平滑。有迭代过程，效果比较不错。-A program written by Matlab for image smoothing based mean shift algorithm. Platform: |
Size: 1024 |
Author:Genghis |
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Webmaster will activate your member account after checking your files. If you do not want to upload source code, you can join the [VIP member] to activate your account. Platform: |
Size: 3072 |
Author:alpha |
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Description: A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects,
is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel. The
masking induces spatially-smooth similarity functions suitable for gradient-based optimization, hence, the target localization problem
can be formulated using the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya coefficient as
similarity measure, and use the mean shift procedure to perform the optimization. In the presented tracking examples, the new method
successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data
association techniques is also discussed. We describe only a few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking. Platform: |
Size: 2459648 |
Author:Ali |
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Description: ua University, in 2002 publi
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Author:wibisono |
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Search - mean shift matlab