Distinctive Image Features from Scale-Invariant Keypoints
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92 citations
Cites background or methods from "Distinctive Image Features from Sca..."
...I. INTRODUCTION Stitching multiple images together can create beautiful highresolution panoramas....
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...After extracting invariant scale features, we got potential feature matches by using k-nearest neighbor method, and then remove the mismatches with RANSAC algorithm....
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92 citations
Cites methods from "Distinctive Image Features from Sca..."
...The next step is computing their SIFT descriptors [52], giving a 128-dimensional vector for each local region, which have been shown to outperform other descriptors such as RIFT and SPIN [47]....
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92 citations
Cites background from "Distinctive Image Features from Sca..."
...[25] (b) Scheme of the SURF descriptor....
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...The first one is to a large extent similar to the SIFT descriptor [25]....
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...different traffic scenes, SIFT (Scale-invariant feature transform [25]) turned out to be the most suitable one for reliable TSR....
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92 citations
92 citations
Cites background from "Distinctive Image Features from Sca..."
...…one is the development of invariant feature detectors, also called interest point operators, such as the Förstner (Förstner and Gülch 1987) and Harris (Harries and Stephen 1988) operators, scale-invariant feature transform (SIFT, Lowe 2004) and speeded up robust features (SURF, Bay et al. 2008)....
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References
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