搜索资源列表
59993143imagefusion
- vc6.0，SIFT算法的代码，影像匹配的功能-vc6.0, SIFT algorithm code, the function of image matching
An-Adaptive-Filter-Model-of-Object
- ：针对目标跟踪过程中目标尺度伸缩和姿态形状的变化引起的目标丢失，以及使用单个模型跟踪 机动目标不够理想，提出一种基于SIFT特征的自适应滤波目标跟踪算法。仿真结果表明，该算法在 目标机动时，跟踪性能远优于其它特征匹配算法和多模型算法，而且计算量小，能保证跟踪的实时性。-Abstract：Aim at the lose of target due to scale。invarl’ant，position change and deformation，as welI as dissati
SIFT_VC
- 非常快速高效的SIFT特征检测与匹配算法，用C++与OpecCV实现-SIFT features are very fast and efficient detection and matching algorithms, using C++ implementation with OpecCV
vlfeat-0.9.9
- 基于sift算法的图像匹配。并用RANSEC算法去除错误匹配。最后还给出了sift算法的图像拼接。-Sift-based image matching algorithm. And use RANSEC algorithm to remove false matches. Finally, given the sift algorithm for image stitching.
edge-detection
- 本程序将SIFT与边缘结合起来用来做图像配准 先用SIFT检测关键点 用CANNY算子进行边缘检测 进而优化选取最佳匹配点 进行向量匹配 图像配准。 -The SIFT program used to do with the edge combination image registration using SIFT test first key with CANNY edge detection operator to optimize select the best match point
sift_experiment
- Matlab+C SIFT 特征提取与匹配演示程序 http://download.csdn.net/source/3472933 http://www.pudn.com/downloads372/sourcecode/graph/texture_mapping/detail1607889.html 使用 Matlab+C++混合编程的SIFT特征提取与匹配演示程序，很完整，是 Morton金字塔无缝漫游 GDAL SIFT 照片配准系统 的底层算法，很适合研究改进。使用这个
[code]sift_win
- 基于opencv编写的SIFT提取和匹配算法，可以在两幅图中找到对应，并计算仿射变换。 内带说明文档，注解详尽-Opencv SIFT written based on extraction and matching algorithms that can find the corresponding figure in two, and calculate the affine transformation. Documentation within the band, detailed
SIFT_VC
- 本代码提供了SIFT算法提取特征点的同时又进行特征点匹配工作，同时还有相关注释说明-The code provides a SIFT algorithm to extract feature points matching feature points also work, as well as the relevant explanatory notes
Sift_technology_notes
- SIFT的技术文档，SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点，其匹配能力较强，可以处理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题，甚至在某种程度上对任意角度拍摄的图像也具备较为稳定的特征匹配能力-SIFT feature matching algorithm is matching feature points at home and abroad in the research field of the hot issues and difficulties,
SIFT_relevant_papers
- SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点，其匹配能力较强，可以处理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题，甚至在某种程度上对任意角度拍摄的图像也具备较为稳定的特征匹配能力。-SIFT feature matching algorithm is matching feature points at home and abroad in the research field of the hot issues and difficulties, and the m
sift_feature-extract-and-match
- 使用sift算法，找出图像的关键点，使用关键点作为匹配因子对两幅图像进行匹配，数据库中包含了丰富的可用图片库。-Use sift algorithm to find the image of the key points, key points to use as matching factor of two images match, the database contains a wealth of available gallery.
sift_search_matching
- 实现sift特征点的提取和匹配，并将匹配点输出到MAT文件-Realization of SIFT feature point extraction and matching, and will match the output to a MAT file
image-matching1
- 基于SIFT的图像匹配，只做了特征点检测，其中在特征点描述子方面做了一点小小的改进-SIFT based on the image matching, only do the feature point detection, which in a feature point descr iptor in a little improvement
KNN-ALG
- 基于欧式距离的最邻近改进算法，该算法在提高SIFT算法的特征点匹配效率-Euclidean distance based on the nearest improved algorithm SIFT algorithm to improve the efficiency of matching feature points
a222
- 基于SIFT特征匹配算子的三维重建方法研究.Based on SIFT feature matching 3D reconstruction method research.-Based on SIFT feature matching 3D reconstruction method research.
LDAHash
- SIFT经LDA，然后二值化形成简短的特征，以提高匹配速度、减少存储量；该特征在Low False Positive 段，性能比SIFT好，但需要训练。-SIFT by the LDA, and then binarization formation of short features, in order to improve the matching speed, reduce the amount of storage the characteristics of the Low, Fal
objectmatch
- 论文，摄像机之间基于区域SIFT描述子的目标匹配，可以参考。-Thesis，the title is "objective matching based on local SIFT descr iptor between different camera"
disparity-200712.2
- 使用sift特征对两幅图像进行匹配，标记出特征点以及匹配上的点-Use sift features on the two images matching, and mark out and matching feature points on the point
ICIS-TONG
- My presentation consists of four main parts. At first, I will introduce some problems of face recognition techniques including general SIFT based methods and the proposed SIFT classification method to solve the problem. And then the propo
pcgames_DotA_im_3.80
- sift匹配程序在matlab环境下的实现，包括特征提取与匹配-the sift match program realization in Matlab environment, including feature extraction and matching