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Description: A lightweight SIFT-implementation for Java after the paper of David Lowe (2004). The ImageJ plugin can be used for rigidly aligning image stacks.
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Author: chenglong |
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Description: 1999年British Columbia大学大卫.劳伊（David G.Lowe）教授总结了现有的基于不变量技术的特征检测方法，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（尺度不变特征变换），这种算法在2004年被加以完善。
-University of British Columbia 1999, David Rowe (David G. Lowe) summed up the professor is not variable based on existing technology, feature detection methods, and formally proposed based on scale space for image scaling, rotation or even affine transform the image to maintain local features invariant description operator-SIFT (Scale Invariant Feature Transform), this algorithm is to be improved in 2004.
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Author: chenping |
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Description: 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 algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.[1]
Applications include object recognition, robotic mapping and navigation, image stitching, 3D modeling, gesture recognition, video tracking, and match moving.
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Author: 张博 |
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Description: 尺度不变特征转换是一种计算机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。程序已调通，在match.m中改变所处理图片的名称即可。相关参考文献已上传本网站，Distinctive Image Features Scale-Invariant Keypoints
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Author: baishibailing |
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Description: sift算法由 David Lowe 在1999年所发表，2004年完善总结。该压缩文件包括他的经典论文，附带一篇中文翻译但不太准确，仅供参考。其对应开源代码已上传本网站并调通。
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Author: baishibailing |
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Description: SIFT特征（Scale-invariant feature transform，尺度不变特征转换)是一种计算机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。此算法有其专利，专利拥有者为 英属哥伦比亚大学。
局部影像特征的描述-SIFT algorithm
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Author: 李小龙 |
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Description: 加拿大University of British Columbia 大学计算机科学系教授 David G. Lowe发表于2004年Int Journal of Computer Vision,2(60):91-110的那篇标题为“Distivtive Image Features from Scale -Invariant Keypoints" 的论文。其程序代码即为上传代码，已经经过本人测试通过。-the code for Distivtive Image Features from Scale-Invariant Keypoint is written by David G. Lowe,which is verified and can operate successfully.
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Author: gaoke |
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Description: 一个图像识别算法.SIFT综述
尺度不变特征转换(Scale-invariant feature transform或SIFT)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。-A kind of algorithm for the image recognition.
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Author: 钟小江 |
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Description: SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。[1] 该方法于1999年由David Lowe[2] 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004年再次经David Lowe整理完善后发表于International journal of computer vision（IJCV）。截止2014年8月，该论文单篇被引次数达25000余次。-SIFT, namely Scale Invariant Feature Transform (Scale-invariant feature transform, SIFT), it is a description for image processing. This description has scale invariance, can detect critical point in the image, it is a local feature descriptor. [1] The method in 1999 by David Lowe [2] First published in the International Conference on Computer Vision (International Conference on Computer Vision, ICCV), 2004 was again perfect finishing after David Lowe published in the International journal of computer vision (IJCV) . As of August 2014, the paper cited the number of times a single article of more than 25,000 times.
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Author: terigen |
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Description: SIFT是由UBC（university of British Column）的教授David Lowe 于1999年提出， 并在2004年得以完善的一种检测图像关键点（key points , 或者称为图像的interest points(兴趣点) )， 并对关键点提取其局部尺度不变特征的描绘子， 采用这个描绘子进行用于对两幅相关的图像进行匹配（matching）。 目前， SIFT可以说是所有图像局部特征描述特征子 中最火的一个了。-SIFT was developed by David Lowe, a professor at UBC (University of British Column) in 1999, and developed a key point (or interest points) of the image in 2004, and A sketch of the local scale invariant feature is extracted the key point, and the descriptor is used to perform matching on the two related images. At present, SIFT can be described as one of the hottest features of all local image features.
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Author: 刘超蝶 |
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Description: %this code is the Matlab implimentation of David G. Lowe,
%"Distinctive image features from scale-invariant keypoints,"
%International Journal of Computer Vision, 60, 2 (2004), pp. 91-110.
%this code should be used only for academic research.
%any other useage of this code should not be allowed without Author agreement.
% if you have any problem or improvement idea about this code, please
% contact with Xing Di, Stevens Institution of Technology. xdi2@stevens.edu
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Author: arzehgar
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Description: 原版的SIFT算法。SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。 该方法于1999年由David Lowe 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004年再次经David Lowe整理完善后发表于International journal of computer vision（IJCV） 。截止2014年8月，该论文单篇被引次数达25000余次(SIFT, the scale invariant feature transform (Scale-invariant feature transform, SIFT), is a description for image processing This description is scale invariant, and it can detect key points in images. It is a local feature descriptor. The method was first published by David Lowe in International Conference on Computer Vision (ICCV) in 1999. In 2004, it was finished by David Lowe again and was published in International Journal of computer vision (IJCV). As of August 2014, the citation number is more than 25000 times)
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Author: fade-war
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Description: 尺度不变特征转换(Scale-invariant feature transform或SIFT)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。(SIFT predicts whether an amino acid substitution affects protein function. SIFT prediction is based on the degree of conservation of amino acid residues in sequence alignments derived from closely related sequences, collected through PSI-BLAST. SIFT can be applied to naturally occurring nonsynonymous polymorphisms or laboratory-induced missense mutations.)
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Author: lllllliiiii |
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