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Description: 使用薄板样条函数，完成点对的非刚体配准方法。此类提供算法的封装。-use thin-plate spline function, the completion point of the non-rigid registration method. Algorithm for such packaging.
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Size: 2743 |
Author: 方宝玉 |
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Description: 使用颜色直方图特征的经典mean shift跟踪目标，文献Real-time tracking of non-rigid objects using mean shift,D Comaniciu, 2003
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Author: lhc_gucas |
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Description: This a collection of utilities for warping of MRI image volumes.
See the man pages for documentation.
The warp method is described in detail in the following paper
Enhancing the Multivariate Signal of 15-O water PET Studies With a
New Non-Linear Neuroanatomical Registration Algorithm
IEEE Transactions on Medical Imaging, 1999, 18(6), p306-19
-This a collection of utilities for warpi Vi of MRI image volumes. See the man pages for doc umentation. The warp method is described in det annexed in the following paper Enhancing the Multiv ariate Signal of 15-O water PET Studies With a Ne w Non-Linear Registration Al Neuroanatomical gorithm IEEE Transactions on Medical Imaging, 1999, 18 (6), p306-19
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Author: 胡顺波 |
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Description: 使用薄板样条函数，完成点对的非刚体配准方法。此类提供算法的封装。-use thin-plate spline function, the completion point of the non-rigid registration method. Algorithm for such packaging.
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Size: 2048 |
Author: 方宝玉 |
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Description: 基于matlab 图像配准 利用非刚性强壮点匹配法匹配两幅图像的一个解约方案-Matlab-based image registration using robust non-rigid point matching method to match two images of a termination program
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Size: 46080 |
Author: wang |
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Description: 最大流最小割算法，可以跟踪主动镜头下的非刚体目标！-Maximum flow minimum cut algorithm, the camera can track the initiative of non-rigid target!
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Size: 9216 |
Author: zry |
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Description: nonrigid_version10: Registration of two 2D images or 3D volumes both rigid and non-rigid with smooth b-spline grid without landmarks
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Author: zhangxq |
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Description: edited by Joseph Hajnal, David Hawkes and Derek Hill. Part 1. Methodology.Part 2. Applications of rigid-body registration.Part 3. Techniques and applications of non-rigid registration
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Author: 陈晨 |
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Description: 非刚性图像配准算例，包括最速梯度下降优化、二次样条、2D/3D配准、互信息最小化、3D仿射等多种配准算法。
非刚性配准是当前应用最多的配准方法，用于处理有较大位移的配准问题-Non-rigid image registration examples, including the steepest gradient descent optimization, quadratic spline, 2D/3D registration, mutual information minimization, 3D affine registration algorithm, etc.. Non-rigid registration is currently the most widely used registration methods used to deal with a greater displacement of registration problems
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Author: zhangji |
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Description: A new approach toward target representation and localization, the central component in visual tracking
of non-rigid 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 few of the potential applications: exploitation of background information,
Kalman tracking using motion models, and face tracking.-A new approach toward target representation and localization, the central component in visual trackingof non-rigid objects, is proposed. The feature histogram based target representations are regularizedby spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functionssuitable for gradient-based optimization, hence, the target localization problem can be formulated usingthe basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyyacoefficient as similarity measure, and use the mean shift procedure to perform the optimization. In thepresented 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 alsodiscussed. We describe only few of the potential applications: exploitation of background information, Kalman tracking using motion models, and face tracking .
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Description: 这是一篇对于SIFT算法应用于非刚性图像配准的论文，相当不错-This is one for the SIFT algorithm is applied to non-rigid image registration of papers, quite good
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Author: 黄显武 |
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Description: 提出一种新的目标表示和定位方法,该方法是非刚体跟踪的核心技术.利用均质空间掩膜规范基于特征直方图的目标表示,该掩膜引入了适合于梯度优化的空间平滑相似函数,所以可以将目标定位问题转换为局部极大值求解问题.我们利用从Bhattacharyya系数倒出的规则作为相似度量,利用mean shift procedure完成优化求解.在给出的测试用例中, 本文方法成功解决了相机移动,阴影,以及其他的图象噪声干扰.文章对运动滤波和数据关联技术的集成也进行了讨论.-A new objective and positioning method to track non-rigid body' s core technology. Standardizing the use of homogeneous space mask the characteristics of histogram based on the objectives that the mask is suitable for the introduction of gradient optimization is similar to spatial smoothing function, Therefore, targeting the problem can be converted to solve the problem of local maxima. We poured from the rules of Bhattacharyya coefficient as similarity measure, using mean shift procedure for solving optimization. give the test cases in, the method succeeded in solving the camera Mobile, shadows, and other image noise. article on the campaign filtering and data association techniques of integration were also discussed.
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Author: maolei |
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Description: (有源代码)数值分析作业,本文主要包括两个部分,第一部分是常微分方程(ODE)的三个实验题,第二部分是有关的拓展讨论,包括高阶常微分的求解和边值问题的求解(BVP).文中的算法和算例都是基于Matlab计算的.ODE问题从刚性(STIFFNESS)来看分为非刚性的问题和刚性的问题,刚性问题(如大系数的VDP方程)用通常的方法如ODE45来求解,效率会很低,用ODE15S等,则效率会高多了.而通常的非刚性问题,用ODE45来求解会有很好的效果.从阶次来看可以分为高阶微分方程和一阶常微分方程,高阶的微分方程一般可以化为状态空间(STATE SPACE)的低阶微分方程来求解.从微分方程的性态看来,主要是微分方程式一阶导系数大的时候,步长应该选得响应的小些.或者如果问题的性态不是太好估计的话,用较小的步长是比较好的,此外的话Adams多步法在小步长的时候效率比R-K(RUNGE-KUTTA)方法要好些,而精度也高些,但是稳定区间要小些.从初值和边值来看,也是显著的不同的.此外对于非线性常微分方程还有打靶法,胞映射方法等.而对于微分方程稳定性的研究,则诸如相平面图等也是不可缺少的工具.值得提出的是,除了用ode系类函数外,用simulink等等模块图来求解微分方程也是一种非常不错的方法,甚至是更有优势的方法(在应用的角度来说).-(Source code) numerical analysis homework, this docment includes two parts, the first is ordinary differential equations (ODE) of the three examples, the second part is about the expansion of the discussion, including the higher-order ordinary differential & boundary value solution Problems (BVP). the text of the algorithm and numerical examples are based on the Matlab. ODE from the rigid (STIFFNESS) look into the issue of non-rigid and rigid problem, rigid problems (such as large coefficient VDP equation) such as using the always method ODE45 used to solve the problems , efficiency will be low, with ODE15S the other hand, many of the high efficiency. and the usual problem of non-rigid, there will be used to solve ODE45 very good results. Judging from the order can be for high-order differential equations and first-order ordinary differential equations, higher-order differential equations can be transformed into a general state space (STATE SPACE) used to solve the low-order different
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Author: wjl |
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Description: 一种非刚体目标的实时检测与跟踪算法。提出了一种复杂背景下自动、实时地检测和跟踪非刚体目标算法-The goal of a non-rigid real-time detection and tracking algorithm. Made against the background of a complex automatic, real-time detection and tracking non-rigid algorithm goal
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Size: 139264 |
Author: 谭园芳 |
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Description: thin plate spline（薄板样条）模型，将已知图像通过非刚性变换得到所需要的图像，在图像配准中非常有用。-thin plate spline (thin plate spline) model, will be known through non-rigid image transformation to be necessary by the images of image registration in very useful.
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Size: 45056 |
Author: 季全 |
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Description: 一种运用边缘矢量场的图象分割算法得到连续的边缘信息并做跟踪.-This image segmentation utilizes an edge vector field (EVF) within the curve evolution framework by using both color and texture features.
The JSEG segmentation aims to achieve consistent segmentation and tracking results for scenes with arbitrary non-rigid object motion.
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Author: dianalee |
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Description: 本书详细介绍了医学图像注册方面的知识，包括配准的原理、刚性配准、非刚性配准，对于医学图像处理方面的研究具有很重要的参考价值。-The book details the registration of medical image information, including the principle of registration, rigid registration, non-rigid registration for medical image processing research has important reference value.
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Size: 5411840 |
Author: 郭静 |
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Description: 主要介绍了当前图像配准的情况，并介绍了非弹性图像配准，是一篇很好的参考文献-Introduces the current situation in image registration, and introduced the non-elastic image registration, is a good reference
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Size: 484352 |
Author: 潘雨 |
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Description: 非刚性和刚性微分方程。非刚性问题的例子，刚性方程的例子-Non rigid and stiff differential equations. Examples of non rigid problems, examples of rigid equations
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Size: 12288 |
Author: 潘 |
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Description: non rigid objetcs tracking
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Author: Amal IEEE
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