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Julia3D
- java做的一个3D动画，根据Julia集画的一个分形图形，能够在Applet容器中由大变小直至消失，然后出现从小变大，循环往复。-do a 3D animation, according to Julia Sets painting a fractal graphics, in Applet container into small until disappear, and then there appears small change, cycles.
Xmipp-0.9.1.tar
- XMIPP is a specialized suite of image processing programs primarily aimed at obtaining the three-dimensional reconstruction of biological specimens from large sets of projection images obtained by transmission electron microscopy. //专门处理图像程序
stanford+rabbit
- stanford大学的兔子，很有名的数据集，搞计算机图形学的人士都知道的-stanford University of rabbits, the well-known data sets and engage in computer graphics people are aware of
udpoint
- The Hammersley and Halton point sets, two well known low discrepancy sequences, have been used for quasi-Monte Carlo integration in previous research. A deterministic formula generates a uniformly distributed and stochastic-looking sampling pattern,
cqr
- OPENGL在圆柱体中心差集 -OPENGL difference set in the center cylinder in the cylinder centers OPENGL Difference Sets
PointList-ApproximateEllipse
- 用C++语言生成三维数据集，椭圆形螺旋形状-In C++ language generation three-dimensional data sets, oval-shaped spiral shape
importance-driven-rendering
- Importance-Driven Volume Rendering(IDVR)是对直接体绘制算法的一个改进，里面集成了各种直接体绘制算法，MIP，two level，IDVR等。有源代码，说明文档，论文，测试数据，帮助文档等。对深入了解直接体绘制有很大帮助。-This report presents an effi cient implementation using (Importance-Driven Volume Rendering- IDVR) t
Ransac
- RANSAC为RANdom SAmple Consensus的缩写，它是根据一组包含异常数据的样本数据集，计算出数据的数学模型参数，得到有效样本数据的算法。它于1981年由Fischler和Bolles最先提出[1]。 RANSAC算法经常用于计算机视觉中。例如，在立体视觉领域中同时解决一对相机的匹配点问题及基本矩阵的计算。 RANSAC算法的基本假设是样本中包含正确数据(inliers，可以被模型描述的数据)，也包含异常数据(Outliers，偏离正常范围很远、无法适应数学模型的数据)
PoissonRecon
- Poisson surface reconstruction creates watertight surfaces from oriented point sets. In this work we extend the technique to explicitly incorporate the points as interpolation constraints. The extension can be interpreted as a generalization of
Action_Recognition-master
- HDMB51数据集以及在此数据集的算法代码，提取特征C2，是人体行为识别非常有挑战性的数据集。-HDMB51 data sets and algorithm code in this data set, extract features C2, human behavior recognition is very challenging datasets.
ICPdianyunpipei
- 对两组点云数据进行ICP匹配，最近点迭代法，进行点云匹配，含有两组点云数据-Two sets of point cloud data for ICP match
CPP_RANSAC
- 它是基于一组包含异常数据的样本数据集，并计算数据的数学模型参数。这是第一次由Fischler和Bolles 1981提出。ransac是经常使用的计算机视觉。RANSAC假设为一组正确的数据，有一种方法，模型参数的计算。-It is based on a set of sample data sets containing abnormal data, and the mathematical model parameters are calculated. It was first propo