搜索资源列表
Factorization
- Lucas-Kanader-Tomasi Feature Tracker，由运动恢复结构的问题，目的是从一组由摄像机移动获得的图像来恢复一个场景的立体结构。对于这个问题，C.Tomasi和T.Kanade[1]于1992年提出了一种Factorization的方法，可以有效地避免噪声的干扰，同时不会受限于特定的运动模型，例如单纯的平移或是旋转。-Lucas-Kanader-Tomasi Feature Tracker, by the movement to restore the structu
kolmog
- 给定任意一个子波，通过克基霍夫变换返回最小相位子波。-Kolmogoroff spectral factorization. Given an arbitrary wavelet this function retrieves the minimum phase wavelet using Kolmogoroff factorization
Vision
- Computer Vision algorithms and applications provides a total operation count for Cholesky factorization.
factorization-20041217.tar
- 在VC++平台上實作以單幅2維相片重建三維建築物模型-With a single photo in VC++ platform to implement image-based graphics, and three-dimensional reconstruction of the building, for example
cholmod
- 常用的优化算法工具包（Cholesky factorization）-a sparse Cholesky factorization and modification package
Incremental-NMF-by-Serhat-S
- 由外国专家Serhat S. Bucak编写的代码，关于增量式非负矩阵分解，还有例子，比较好用。-The code, written by foreign experts Serhat S. Bucak incremental non-negative matrix factorization, there are examples of relatively easy to use.
Shape-and-Motion-from-Image-Streams
- 运动的仿射结构，原理英文pdf和matlab程序-Shape and Motion from Image Streams under Orthography： a Factorization Method
Factorization
- 人脸识别的，一个学长写的，效果还可以,你们可以看一看，是基于神经网络的-Face recognition, an advisor to the written, the effect can be, you can look at, is based on neural network
background
- 无摄像机抖动的背景建模方法，使用张量分解，需要张量工具箱的支持。-a background estimation method, using tensor factorization.
motioncompensation
- 一种带有摄像机抖动的背景建模方法，使用张量分解和仿射变换，需要张量工具箱的支持。-a background estimation method with dynamic change,using tensor factorization and affine transform
ADMNMF
- 基于交替方向乘子法的非负矩阵分解算法，主要用于盲分离-Alternating direction multiplier method based on non-negative matrix factorization algorithm, mainly used for blind source separation
TestSVD
- svd矩阵分解源代码，帮助理解svdjar包的使用-svd matrix factorization source code to help understand the use svdjar package
CNMF
- 通过耦合非负矩阵分解，实现高光谱和多光谱图像分类-Coupled Nonnegative Matrix Factorization for HSI and MSI Fusion
NMF_picture
- 非负矩阵分解，对原始图像进行特征提取，也可用于去噪等。-nonegative matrix factorization
fgm_2012_05_12
- 分解图匹配（Factorized Graph Matching）源码-Graph matching (GM) is a fundamental problem in computer science, and it plays a central role to solve correspondence problems in computer vision. GM problems that incorporate pairwise constraints can be formulate
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- 利用GDA方法作为子程序嵌入非负张量分解中(Solving the nonnegative tensor factorization by the Method of GDA)
Total Variation Regularized Reweighted Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing
- Total Variation Regularized Reweighted Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing.By Wei He