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ANN is a library written in the C++ programming language to support both
exact and approximate nearest neighbor searching in spaces of various
dimensions.ANN is also a testbed containing
programs and procedures for generating data sets, collect
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ANN is a library written in the C++ programming language to support both exact and approximate nearest neighbor searching in spaces of various dimensions.
可以直接用于工程 支持 Kd tree，BBF(best bin first)
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The approximate nearest neighbor search code is contained in this zip file. You can use the data contained in to see how the program works.
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c++实现的KNN库:建立高维度的K-d tree,实现K邻域搜索，最小半径搜索-K-NN algorithm implementation.
It supports data structures and algorithms for both exact and approximate nearest neighbor searching in arbitrarily high dimensions.
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由国外著名大学编写的非常有效近似最近邻分类算法的源码与库，可直接使用，也可作为学习-Well-known universities from abroad prepared very effective approximate nearest neighbor classification algorithm source code and libraries, can be used directly, can also be used as study
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FLANN - Fast Library for Approximate Nearest neighbors
This is a library for fast approximate nearest neighbor matching. -FLANN- Fast Library for Approximate Nearest neighbors This is a library for fast approximate nearest neighbor matching.
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本代码是ANN算法求最近元素的实现代码，使用时只需将ANN/ANNx.h包含进去即可-that is a good library to implement the algothrim of approximate nearest neighbor
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code for approximate nearest neighbor algorithm,最经典的近似搜索算法-code for approximate nearest neighbor algorithm
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ANN is a library written in the C++ programming language to support both
exact and approximate nearest neighbor searching in spaces of various
dimensions. It was implemented by David M. Mount of the University of
Maryland, and Sunil Arya of the
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code for approximate nearest neighbor search
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快速计算近似最近邻域，可用于图形处理中计算点云的k-Quickly compute approximate nearest neighbor, can be used for graphics processing point cloud computing knn
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大规模图像检索的代码，matlab与c++混合编程。总结了目前图像检索领域目前主要存在的方法。通过阅读该代码，可以对于经典的“词袋”模型（bow模型）有个具体的了解，但是该代码没有提供前序的特征提取，是直接从对提取好的特征向量聚类开始的，包括了k-means，分层k-means（HKM）聚类，倒排文件的建立和索引等，该代码还提供了局部敏感哈希（LSH）方法。最后，这份代码是下面这篇论文的作者提供的，
Indexing in Large Scale Image Collections: Sc
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查找二维和三维空间中K最近邻点的算法，在Approximate Nearest Neighbor Searching（ANN）的基础上进行了包装，易于使用。-Find the two-dimensional and three-dimensional space of K nearest neighbor algorithm, Approximate Nearest Neighbor Searching (ANN) based on the packaging.
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Optimized Product Quantization for Approximate Nearest Neighbor Search
Tiezheng Ge, Kaiming He, Qifa Ke, and Jian Sun
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013
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用LSH算法实现近似最近邻检索，并提高了效率-With LSH algorithm approximate nearest neighbor search, and improves efficiency
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This toolbox contains C++ files that implement the
Approximate Nearest Neighbor Library (ANN)
and and its utility functions in matlab.
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The code implements a coarse-to-fine variational framework for optical flow estimation between two image frames that incorporates descr iptor matches in additiona to the standard brightness and gradient constrancy constraints, for dealing effectively
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针对三维重建中的点云配准问题，提出一种基于点云特征的自动配准算法。利用微软Kinect传感器采集物
体的多视角深度图像，提取目标区域并转化为三维点云。对点云进行滤波并估计快速点特征直方图特征，结合双向
快速近似最近邻搜索算法得到初始对应点集，并使用随机采样一致性算法确定最终对应点集。根据奇异值分解法
求出点云的变换矩阵初始值，在初始配准的基础上运用迭代最近点算法做精细配准。实验结果表明，该配准方法既
保证了三维点云的配准质量，又降低了计算复杂度，具有较高的可操作性和鲁棒性。
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使用FLANN(近似最近邻算法)实现图像特征的匹配，其中图像特征使用SIFT提取，算法能实现单应性匹配需求。-
FLANN (approximate nearest neighbor algorithm) is used to match the image feature, and the image feature is extracted using SIFT. The algorithm can achieve the homography matching requirement.
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