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Apply David Lowe s Scale Invariant Feature Transform (SIFT) algorithm to a grayscale image.
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this programme implements David Lowe s Scale Invariant Feature Transform (SIFT) algorithm to a grayscale image
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采用改进的尺度不变特征变换算法计算物体旋转角度-The improved scale-invariant feature transform algorithm to calculate the object rotation
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尺度不变特征变换（SIFT算法）Matlab 程序代码-Scale-invariant feature transform (SIFT algorithm) Matlab code
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SIFT特征（Scale-invariant feature transform，尺度不变特征转换)是一种电脑视觉的算法用来侦测与描述影像中的局部性特征，它在空间尺度中寻找极值点，并提取出其位置、尺度、旋转不变量，此算法由 David Lowe 在1999年所发表，2004年完善总结。其应用范围包含物体辨识、机器人地图感知与导航、影像缝合、3D模型建立、手势辨识、影像追踪和动作比对。-Scale-invariant feature transform (or SIFT) is an algori
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This paper investigates a new face recognition system based on an efficient design of MLP classifier using each SIFT (Scale Invariant Feature Transform) keypoint as feature.
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This paper investigates a new face recognition system based on an efficient design of classifier using SIFT (Scale
Invariant Feature Transform) feature keypoint. This proposed system takes the advantage of SIFT feature which possess strong
robust
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Sift算子最早是由D.G.Lowe于1999年提出的，当时主要用于对象识别。
2004年D.G.Lowe对该算子做了全面的总结，并正式提出了一种基于尺度空间的、对图像缩放、旋转甚至仿射变换保持不变性的图像局部特征描述算子sift（Scale Invariant Feature Transform)算子，即尺度不变特征变换。-Sift child the first count by DGLowe in 1999, was mainly used for object recognition
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尺度不变特征变换匹配算法 ppt格式 算法讲解-Scale Invariant Feature Transform （SIFT）
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The SIFT algorithm[1] takes an image and transforms it into a collection of local feature vectors.
Each of these feature vectors is supposed to be distinctive and invariant to any scaling, rotation or
translation of the image. In the original i
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sift算法 图像处理 尺度无关特征转换 matlabSIFT算法的主要思想是在尺度空间寻找极值点，然后对极值点进行过滤，找出稳定的特征点。最后在每个稳定的特征点周围提取图像的局部特性，形成局部描述子并将其用在以后的匹配中.-Scale Invariant Feature Transform (SIFT) is an
approach for detecting and extracting local feature
descr iptors that are reasonably i
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Histogram of Oriented Gradients (HOG) are feature descr iptors used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized portions of an image. This method i
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The Scale-Invariant Feature Transform (SIFT) bundles a feature detector and a feature descr iptor. The detector extracts from an image a number of frames (attributed regions) in a way which is consistent with (some) variations of the illumination, vi
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从国外图像处理牛人的网址上下载来的程序，主要介绍的是SIFT算法即尺度不变特征变换算法，用于图像处理，很完善的程序，大家可以借鉴学习下。-Download from the URL of the the foreign image processing cattle people to the program, introduces SIFT algorithm namely Scale Invariant Feature Transform algorithm for image proces
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针对sift特点应用到了配准算法里去，并且可应用与可见光与红外光的配准中去-In this paper, SIFT( Scale Invariant Feature Transform) feature, which has shown great success
in computer vision, is introduced into image registration in remote sensing. In addition, we also p roposed a
fea
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尺度不变特征变换（SIFT）算法详解及C++修正后源码-Scale Invariant Feature Transform (SIFT) Algorithm explain and C++ of correction after source
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SIFT特征（Scale-invariant feature transform，尺度不变特征转换)-failed to translate
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本文在在尺度不变特征变换(Scale invariant feature transform,SIFT)特征匹配算法的基础上, 提出了一种基于累积特征的多目标的跟踪算法, 通过对目标的SIFT特征进行实时更新来去除由噪声(或形变)带来的\过时"特征信息, 保证了特征的稳定, 提高了匹配准确度. 实验结果表明, 本算法能够有效处理目标由于旋转、形变而导致跟踪性能下降甚至跟踪目标丢失的问题, 同时对跟踪过程中多目标的关联, 也具有较好的鲁棒性.-In this paper, the Scale In
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一种常用于图像特征描述的一种描述子，全称尺度不变特征变换-Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.[1]
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low sift算法的实现，可以提取一个图像的特征点，也可以实现图像之间的特征点匹配-Scale-Invariant Feature Transform
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