Tag Archives: SIFT


SURF (Speeded Up Robust Features), is a feature detector, we talked about SIFT before, and SURF is sort of derivative of SIFT. SURF is based on sums of 2D Haar wavelet responses and makes an efficient use of integral images. I’ll not represent the whole story of SURF, because its idea is very similar to SIFT, so […]

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I’m working on a project which is something like Bundler with my team, our aim is using different images of an object (we only have images, and know nothing about the positions these images took or parameters of cameras), to re-construct the 3-D module of the object. In this project, I used RANSAC on calculating homographies […]

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SIFT (Scale-invariant feature transform) is one of popular feature matching algorithms, it is good because of its several attributes. There are kinds of primitive ways to do image matching, for some images, even compare the gray scale value pixel by pixel works well. However, what if features in images are in different scales? What if features are […]

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