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基于Sift算法开发商标图案匹配程序，(1)各个CBIR模块及其技术；
(2)Sift算法及其在图像匹配、目标识别中的应用；
(3)Sift算法在图像检索中的应用。
-Sift algorithm development based on pattern matching program mark (1) Each CBIR module and its technology (2) Sift algorithm and its application in image ma
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Detecting, identifying, and recognizing salient regions or feature points
in images is a very important and fundamental problem to the computer vision
and robotics community. Tasks like landmark detection and visual odometry,
but also object re
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基于NewMikolajczykDetector产生的.sift文件的特征点匹配！-Image matching and object recognition Based on .sift file generated by NewMikolajczykDetector
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Scale Invariant Feature Transform (SIFT) has shown to be very powerful for general object detection/recognition. And recently, it has been applied in face recognition. This is the matlab code.
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SIFT算法小结.doc
Snake算法用于图像分割.doc
一种立体视觉系统的研发项目申报书.doc
颜色纹理识别.doc
运动目标的稳健匹配系统.doc
-Summary SIFT algorithm. Doc Snake algorithm for image segmentation. Doc a stereo vision system returns R & D projects. Doc color texture recognition. Doc ro
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david lowe article about sift object recognition from sift D.G.LOWE-david lowe article about sift object recognition from sift D.G.LOWE
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基于局部特征的目标识别的ppt，国外大牛lowe的ppt-Object Recognition from Local Scale-Invariant Features
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sift的详细介绍，主要步骤是：1.关键点检测2.关键点描述 3.关键点匹配 4.消除错配点。物体识别的必备资料
-sift the details, the main steps are: 1. The key point detection (2) describe key 3 key match 4 to eliminate the mismatch point. Essential information on object recognition
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基于shif的物体识别源码
基于shif的物体识别源码-SIFT based object Recognition
SIFT based object Recognition
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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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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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SURF_DETECTOR
SURF (Speeded Up Robust Feature) is a robust image detector and descr iptor, first presented by Herbert Bay et al. in 2006, that can be used in computer vision tasks like object recognition or 3D reconstruction. It is partly inspired
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Implementation of Parallel edition of SIFT algorithm discussed in Parallelism of Vision-based Algorithms
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物体识别算法SIFT的研究sift算法的特征提取和匹配-Sift algorithm of object recognition algorithm SIFT feature extraction and matching
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SIFT 算法提取图像局部特征， 成功应用于物体识别、图像检索等领域。SIFT 算法主要分为四个步骤： 检测尺度空间极值点、精确定位极值点、为每个关键点指定方向参数、关键点描述子的生成。-SIFT algorithm to extract local image features, successfully applied to object recognition, image retrieval and other fields. SIFT algorithm is divided into
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SIFT(Scale Invariant Feature Transform)即尺度不变特征变换，是 D. G.Lowe 在 1999 年提出的一种基于图像局部特征的描述算子，并于 2004年做了完善。SIFT算法是一种基于线性尺度空间，对图像缩放、旋转甚至仿射变换保持不变的局部特征描述算子，因此被广泛地应用于机器人定位、导航和地图生成中。-This paper presents a method for extracting distinctive invariant features fro
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sift算法的matlab实现，作者Lowe的源码，用于目标识别-sift algorithm,run by matlab,produced by Lowe,for object recognition.
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SIFT 特征提取 简单实用 可用于人脸特征分析以及其他物体识别领域-SIFT feature extraction is simple and practical facial feature can be used for analysis, and other areas of object recognition
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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 na
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SIFT匹配（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，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。-Matching SIFT (Scale invariant feature transform, Scale invariant feature transform) is a co
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