Description: Active Shape Models 的创始人 T.F.Cootes的几篇重要论文-the founder of the T. F. Cootes several important papers Platform: |
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Author:rllzyy |
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Description: 在源码实现的研究过程中将采取基于水平集方法的几何活动轮廓模型如测地轮廓模型或Mumford-shah模型与其他的分割方法的结合。针对具体的图像可以将一些先验知识（灰度和形状信息）加入到算法中-source realized in the course of the study will be taken based on the level set method of the geometric active contour models such as the geodesic contours Die Mumford- or-shah model and the other a combination of segmentation. Specific image may be some a priori knowledge (gray and shape information) to join algorithm Platform: |
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Author:牛牛 |
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Description: Active Shape Models 的创始人 T.F.Cootes的几篇重要论文-the founder of the T. F. Cootes several important papers Platform: |
Size: 3383296 |
Author:rllzyy |
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Description: 图像处理的关于Snakes : Active Contour Models算法和水平集以及GVF的几篇文章，文章列表为：
[1]Snakes Active Contour Models.pdf
[2]Multiscale Active Contours.pdf
[3]Snakes, shapes, and gradient vector flow.pdf
[4]Motion of level sets by mean curvature I.pdf
[5]Spectral Stability of Local Deformations Spectral Stability of Local Deformations.pdf
[6]An active contour model for object tracking using the previous contour.pdf
[7]Volumetric Segmentation of Brain Images Using Parallel Genetic AlgorithmsI.pdf
[8]Segmentation in echocardiographic sequences using shape-based snake model.pdf
[9]Active Contours Without Edges.pdf
学习图像处理的人必看的几篇文章-Image Processing on the Snakes: Active Contour Models and Level Set algorithm, as well as several articles of the GVF, the list for the article: [1] Snakes Active Contour Models.pdf [2] Multiscale Active Contours.pdf [3] Snakes, shapes, and gradient vector flow.pdf [4] Motion of level sets by mean curvature I.pdf [5] Spectral Stability of Local Deformations Spectral Stability of Local Deformations.pdf [6] An active contour model for object tracking using the previous contour.pdf [7 ] Volumetric Segmentation of Brain Images Using Parallel Genetic AlgorithmsI.pdf [8] Segmentation in echocardiographic sequences using shape-based snake model.pdf [9] Active Contours Without Edges.pdf learning image processing articles were a must-see Platform: |
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Author:张阳 |
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Description: ASM是由Cootes和泰勒推出的多分辨率方法的一个例子。
基本思想：
在ASM模型训练，训练从手工绘制的图像轮廓。发现的ASM模型在训练使用主成分分析（PCA），使该模型自动识别数据的主要变化是，如果可能的轮廓/好的对象的轮廓。还包含了ASM模型的协方差矩阵描述行垂直纹理口岸时，在正确的位置。
-Description This is an example of the basic Active Shape Model (ASM) as introduced by Cootes and Taylor, with multi-resolution approach.
Basic idea:
The ASM model is trained from manually drawn contours in training images. The ASM model finds the main variations in the training data using Principal Component Analysis (PCA), which enables the model to automatically recognize if a contour is a possible/good object contour. Also the ASM models contains covariance matrices describing the texture of the lines perpendicular to the control points when in the correct positions.
After creating the ASM model, an initial contour is deformed by finding the best texture match for the control points. This is an iterative process, in which the movement of the control points is limited by what the ASM model recognizes from the training data as a "normal" object contour.
Literature:
- Ginneken B. et al. "Active Shape Model Segmentation with Optimal Features", IEEE Transactions on Medical I Platform: |
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Author:谢冉 |
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Description: this code in matlab for applying active shape models and active appearance models to detect the features of hand-this code in matlab for applying active shape models and active appearance models to detect the features of hand Platform: |
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Author:gnagi |
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Description: vialo-jones人脸检测和识别算法的c参考实现，适合移植到多个平台-These are the source files for stasm, which is a command line program
for locating features in a face using Active Shape Models. You give
stasm an image file (i.e. a JPEG or BMP) and it returns the image with
the facial features marked out on the image. It also returns the coordinates of the face landmarks in the file "log" Platform: |
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Author:jam |
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Description: 主动形状模型实现与多分辨率统计；ASM实现人脸的定位匹配,算法简单.-
Active Shape Models Implementation
with Multi-Resolution Statistics；
ASM can realize face location and matching.Algorithm is simple. Platform: |
Size: 24576 |
Author:柯柯范儿 |
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Description: Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which is promising in exposing the more complicated correlation between original high-dimensional features. In this paper, we first talk about the basic ideas of PCA and kernel PCA, and then focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied to improve traditional ASMs. Then we show some experiment results to compare the performance of kernel PCA and traditional PCA for pattern classification. We also implement the kernel PCA-based ASMs, and use it to construct human face models. Platform: |
Size: 403456 |
Author:Shinva |
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Description: Active shape models (ASMs) are statistical models of the shape of objects which iteratively deform to fit to an example of the object in a new image, developed by Tim Cootes and Chris Taylor in 1995. Platform: |
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Author:huang d d |
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Description: this principle component analysis(PCA) that is used for linear dimensionality reduction and feature extraction as well as the nonlinear form of PCA which is KPCA and how PCA is used for Active shape models -this is principle component analysis(PCA) that is used for linear dimensionality reduction and feature extraction as well as the nonlinear form of PCA which is KPCA and how PCA is used for Active shape models Platform: |
Size: 7238656 |
Author:ghazal |
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