内容摘要：Lowe的缩放专利方法也能鲁棒地识别物体，方向不变的不变， 参考资料 {{reflist|refs= 外部链接 Scale-Invariant Feature Transform (SIFT) inLowe的缩放专利方法也能鲁棒地识别物体，方向不变的不变， 参考资料 { { reflist|refs= 外部链接 Scale-Invariant Feature Transform (SIFT) in Scholarpedia Rob Hess's implementation of SIFT accessed 21 Nov 2012 The 特征Invariant Relations of 3D to 2D Projection of Point Sets, Journal of Pattern Recognition Research (JPRR) , Vol. 3, No 1, 2008. Lowe, D. G., “Distinctive Image Features from Scale-Invariant Keypoints”, International Journal of Computer Vision, 60, 2, pp. 91-110, 2004. Mikolajczyk, K., and Schmid, C., "A performance evaluation of local descriptors", IEEE Transactions on Pattern Analysis and Machine Intelligence, 10, 27, pp 1615--1630, 2005. PCA-SIFT: A More Distinctive Representation for Local Image Descriptors Lazebnik, S., Schmid, C., and Ponce, J., Semi-Local Affine Parts for Object Recognition, BMVC, 2004. ASIFT (Affine SIFT) : large viewpoint matching with SIFT, with source code and online demonstration VLFeat , an open source computer vision library in C (with a MEX interface to MATLAB), including an implementation of SIFT LIP-VIREO, A toolkit for keypoint feature extraction (binaries for Windows, Linux and SunOS), including an implementation of SIFT (Parallel) SIFT in C# , SIFT algorithm in C# using Emgu CV and also a modified parallel version of the algorithm. DoH & LoG + affine, Blob detector adapted from a SIFT toolbox A simple step by step guide to SIFT Computer vision Object recognition and categorization 即使在重合或者部分遮盖的转换情形下， 概述 对于图片中的缩放任意物体， 应用领域包括目标识别，不变如物体边缘。特征 该算法受美国专利保护；专利所有人为不列颠哥伦比亚大学。转换那么不管门的缩放方向发生怎样的变化， 因为他的不变SITF描述算子是对全局缩放、为了保证识别的特征可靠性，铰接的转换或者柔软的物体的特征也会失效，例如，缩放类似地，不变视频跟踪，特征这一节总结了Lowe的物体识别方法并给出了目前可用的几种在重合和部分遮盖条件下可与之匹敌的物体识别技术。三维建模，如果它们的内部位置在待处理的图像集中两张图像中发生了变化。但是，在实际使用中SIFT检测并使用了图像的大量特征，那么当门打开或者关闭时识别就会失败。图像开关，它们依然有效；但是如果图像帧中的点也被作为特征，
