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surf tracking
- Most motion-based tracking algorithms assume that objects undergo rigid motion, which is most likely disobeyed in real world. In this paper, we present a novel motion-based tracking framework which makes no such assumptions. Object is represented by
hmm
- Runs an HMM as a generative model generating N output vectors
2dgaussian
- 汽车高斯曲面拟合 --- 2程序，以适应到表面二维高斯： 子= A *的进出口（ -（（西为X0）^2/2/sigmax^2 +（艺Y0的）^2/2/sigmay^ 2）。。）+ b的 这些例程是自动在某种意义上说，他们并不需要出发对模型参数的猜测规范。 autoGaussianSurfML（十一，彝，子）适合通过对模型参数的最大似然（最小二乘）。它首先计算了该模型在许多可能的参数值，然后选择最佳质量设置和细化与lsqcurvefit它。 auto
MotionTrackingPOM.pdf
- Given two to four synchronized video streams taken at eye level and from different angles, we show that we can effectively combine a generative model with dynamic programming to accurately follow up to six individuals across thousands of frames i
ITU-R_IMT-A_channel-model
- 一本非常好的关于ITU解说的书籍，通过它可以了解ITU信道的生成原理。-A very good about ITU explain books, by which it can understand the ITU channel generative principle.
3-D-Models-Pose-and-Illumination
- The 3-D Morphable Model was introduced as a generative model to p redictthe appearances o f an individual while using a statistical prior on shape and texture allowin g its parameters to be estimated from single image. Based on these new unde
Multi-Class-Video-Co-Segmentation
- 这是一篇关于多个物体类的协同分割应用到视频分割的论文。-Multi-Class Video Co-Segmentation with a Generative Multi-Video Model ；2013 IEEE Conference on Computer Vision and Pattern Recognition
lda-c
- LDA是一种文档主题生成模型，也称为一个三层贝叶斯概率模型，包含词、主题和文档三层结构。文档到主题服从Dirichlet分布，主题到词服从多项式分布。 LDA是一种非监督机器学习技术，可以用来识别大规模文档集（document collection）或语料库（corpus）中潜藏的主题信息。它采用了词袋（bag of words）的方法，这种方法将每一篇文档视为一个词频向量，从而将文本信息转化为了易于建模的数字信息。但是词袋方法没有考虑词与词之间的顺序，这简化了问题的复杂性，同时也为
JRMPC_v0.9.2
- A Generative Model for the Joint Registration of Multiple Point Sets
daSVM-master
- Matlab implementation of the EM and MCMC algorithm for SVMs as introduced in the paper Data augmentation for support vector machines http://ba.stat.cmu.edu/journal/2011/vol06/issue01/polson.pdf-This is a Matlab implementation of the fancy idea by Pol
Speech Processing Analysis - MATLAB
- The number of states in GMM as the generative model of the frames is obtained using k-means algorithm. This also helps to initialize the mean vector and the covariance matrix of the individual state of the GMM. The training LPC frames collected fro
IDCT_Tracker14
- 代码适用于追踪物体，可以很有效的图中进行精确的实时追踪(This code impelemts a method for tracking an object in a sequence of images given its location in the first frame. In this approach, a combination of generative and discriminative methods is used to model the object appear
adversarial.tar
- 此程序为对抗生成网络，生成图像。 生成对抗网络是一种生成模型（Generative Model），其背后基本思想是从训练库里获取很多训练样本，从而学习这些训练案例生成的概率分布。 而实现的方法，是让两个网络相互竞争，‘玩一个游戏’。其中一个叫做生成器网络（ Generator Network），它不断捕捉训练库里真实图片的概率分布，将输入的随机噪声（Random Noise）转变成新的样本（也就是假数据）。另一个叫做判别器网络（Discriminator Network），它可以同时观察真实和假
lesson51-WGAN实战
- 生成式对抗网络（GAN, Generative Adversarial Networks ）是一种深度学习模型，是近年来复杂分布上无监督学习最具前景的方法之一。模型通过框架中（至少）两个模块：生成模型（Generative Model）和判别模型（Discriminative Model）的互相博弈学习产生相当好的输出。(Emergent against network (GAN, Generative Adversarial Networks) is a kind of deep learni