发明申请
US20100195914A1 SCALABLE NEAR DUPLICATE IMAGE SEARCH WITH GEOMETRIC CONSTRAINTS 有权
可近似的几何图像搜索与几何约束

SCALABLE NEAR DUPLICATE IMAGE SEARCH WITH GEOMETRIC CONSTRAINTS
摘要:
Methods are disclosed for finding images from a large corpus of images that at least partially match a query image. The present method makes use of feature detectors to bundle features into local groups or bundles. These bundled features are repeatable and much more discriminative than an individual SIFT feature. Equally importantly, the bundled features provide a flexible representation that allows simple and robust geometric constraints to be efficiently enforced when querying the index.
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