问题描述
TinEye，谷歌和其他人提供了一个反向图片搜索 - 你可以上传照片，并在几秒钟内就可以找到类似的图片
TinEye, Google and others offer a "reverse image search" -- you can upload a photo and within seconds it will find similar photos.
有没有这些算法的开源版本？
Is there an open-source version of these algorithms?
我知道上海对外贸易等算法寻找外观相似的照片，但他们只对直接比较一张照片到另一个。也就是说，要找到类似的照片，一幅照片，是一个 O（N）操作，找到所有视觉上相似的照片将是为O（n ^ 2 ） - 这两者都是过于缓慢
I know about "SIFT" and other algorithms for finding "visually similar" photos, but they only work for comparing one photo directly to another. i.e., to find similar photos to a given photo is an O(n) operation, to find all visually similar photos would be O(n^2) -- both of which are prohibitively slow.
我需要一个特征描述是可转位由[关系]数据库，以减少结果集的东西更易于管理。
I need a feature descriptor that is indexable by a [relational] database to reduce the result set to something more manageable.
通过外观相似的我的意思的非常的相似。也就是说，已经轻轻一碰了照片/重新着色在Photoshop中，稍稍修剪或调整，拍摄的照片在同一场景中快速连续，或翻转或旋转图像。
By "visually similar" I mean very similar. i.e, a photo that has been lightly touched up/recolored in Photoshop, slightly cropped or resized, photos taken in rapid succession of the same scene, or flipped or rotated images.
推荐答案
您可以考虑的一个有效的方法是袋-of-Words模型。
A valid approach you can consider is the Bag-of-Words model.
基本上你可以做的目标图像脱机计算。您可以从这些图像中提取了一堆功能，以创建一个codebook与像 K-均值聚类算法。搜索最近的影像会导致如最近邻搜索的算法在的codebook空间中的应用
Basically you can do an offline computation of the target images. You can extract from those images a bunch of features in order to create a codebook with algorithms like k-means clustering. Searching for the nearest images will lead to the applications of an algorithm like Nearest neighbor search in the space of the codebook.
有关邻居搜索，您可以使用FLANN
For the neighbour search you can use FLANN
- http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN
- http://opencv.willowgarage.com/documentation/cpp/flann_fast_approximate_nearest_neighbor_search.html
- http://www.cs.ubc.ca/~mariusm/index.php/FLANN/FLANN
- http://opencv.willowgarage.com/documentation/cpp/flann_fast_approximate_nearest_neighbor_search.html
看看还在：视觉相似性搜索算法
这只是一种可能性，真理必须被告知，这个话题实在是充满挑战和litterature它确实是巨大的。
This is only a possibility and, truth must be told, this topic is really challenging and litterature on it is really huge.
只是一些参考：
- http://www.cs.nott.ac.uk/~qiu/webpages/Papers/ColorPatternRecognition.pdf
- http://cs.brown.edu/~th/papers/Hofmann-UAI99.pdf
- http://www.ifp.illinois.edu/~jyang29/ScSPM.htm
- http://johnwinn.org/Publications/papers/Savarese_Winn_Criminisi_Correlatons_CVPR2006.pdf
- http://www-cvr.ai.uiuc.edu/ponce_grp/publication/paper/cvpr06b.pdf
- http://www.cs.nott.ac.uk/~qiu/webpages/Papers/ColorPatternRecognition.pdf
- http://cs.brown.edu/~th/papers/Hofmann-UAI99.pdf
- http://www.ifp.illinois.edu/~jyang29/ScSPM.htm
- http://johnwinn.org/Publications/papers/Savarese_Winn_Criminisi_Correlatons_CVPR2006.pdf
- http://www-cvr.ai.uiuc.edu/ponce_grp/publication/paper/cvpr06b.pdf
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