Description: 这是一个基于非参数模型的背景减运动目标分割算法的VC++程序，自己编写的，上传与大家分享。-This is a non - parametric model based on the background by moving object segmentation algorithm VC procedures, the preparation of their own. Upload share with you. Platform: |
Size: 231138 |
Author:hjs |
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Description: 这是一个基于非参数模型的背景减运动目标分割算法的VC++程序，自己编写的，上传与大家分享。-This is a non- parametric model based on the background by moving object segmentation algorithm VC procedures, the preparation of their own. Upload share with you. Platform: |
Size: 230400 |
Author:hjs |
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Description: 参数活动轮廓模型分割算法，运行稳定，且效果理想-Parametric active contour model segmentation algorithm, running stability, and the results are satisfactory Platform: |
Size: 10605568 |
Author:yanghy |
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Description: 基于形变模型的肺部病灶区域分割与检测方法研究-Deformable model-based segmentation of the lung lesions and detection of Platform: |
Size: 909312 |
Author:李尊 |
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Description: 可以检测图像中圆和直线的信息，有利于初学者使用学习。-Edge detection has played an important role in the field of computer vision. A parametric edge detection method based on recursive mean-separate image decomposition is introduced. A method for automatic parameter selection and two methods for thresholding are also suggested. Experimental results show that the proposed method outperforms many popular edge detection methods, including Sobel, Prewitt, Frei-Chen, and Canny both visually and by quantitative edge map evaluation. Proper parameter selection can also provide segmentation of materials such as potential threat objects in x-ray luggage scan images. Platform: |
Size: 13312 |
Author:力量 |
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Description: 从直线的Cohen-Sutherland、中点分割和参数化裁剪算法中，任选一种，编程实现；
2.编程实现Bezier曲线分割递推de Casteljau算法。
3.任选一种曲面，并编程实现
-From the line of Cohen-Sutherland, the midpoint of segmentation and parametric clipping algorithm, Choose one, programming 2. Programming Recursive Bezier curve segmentation de Casteljau algorithm. 3. Choose one surface, and programming Platform: |
Size: 1024 |
Author:孙伟 |
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Description: This readme describes the Biased and Filtered Point Sampling algorithm.
Before running the code, please run "compile_MEX.m" in the "dependent_files" directory.
BFPS.m is the main file that draws samples. A demo can be run from Matlab with the following command:
>> BFPS(double(imread( im.jpg )), 2, 1, 1, 0, 1)
For faster density estimates in non-parametric image segmentation, the fast Gauss transform can be used in place of Matlab s ksdensity function.
Copyright 2011. MIT. All Rights Reserved. Platform: |
Size: 129024 |
Author:馬英九 |
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Description: CVPR2012_oral
Weakly Supervised Structured Output Learning for Semantic Segmentation-We address the problem of weakly supervised semantic
segmentation. The training images are labeled only by the
classes they contain, not by their location in the image. On
test images instead, the method must predict a class label
for every pixel. Our goal is to enable segmentation algorithms
to use multiple visual cues in this weakly supervised
setting, analogous to what is achieved by fully supervised
methods. However, it is difficult to assess the relative usefulness
of different visual cues from weakly supervised training
data. We define a parametric family of structured models,
where each model weighs visual cues in a different way. We
propose a Maximum Expected Agreement model selection
principle that evaluates the quality of a model from the family
without looking at superpixel labels. Searching for the
best model is a hard optimization problem, which has no
analytic gradient and multiple local optima. We cast it as
a Bayesian optimization problem and propose an Platform: |
Size: 2200576 |
Author:费炳超 |
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Description: this is the first variational image segmentation algorithm that involves region-dependent multi-dimensional descriptors based on the optimal transport theory. The distributions are represented owing to non-parametric kernel density estimators(In this paper, we propose a novel and rigorous framework for region-based active contours that combines the Wasserstein distance between statistical distributions in arbitrary dimension and shape derivative tools. To the best of our knowledge) Platform: |
Size: 836608 |
Author:songggg |
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Search - parametric segmentation