Object recognition from local scale-invariant features
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Cites methods from "Object recognition from local scale..."
...More recently, Lowe [13] describes a Scale Invariant Feature Transform (SIFT) approach where scale-space features are detected and characterised in a manner invariant to location, scale and orientation....
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738 citations
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Cites methods from "Object recognition from local scale..."
...We follow the approach of [21] and represent images using affine covariant regions, described by SIFT [15] descriptors and quantized into approximately 2,000 visual words....
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737 citations
Additional excerpts
...Their approach used SIFT [17] and MKL....
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References
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"Object recognition from local scale..." refers background or methods in this paper
...This allows for the use of more distinctive image descriptors than the rotation-invariant ones used by Schmid and Mohr, and the descriptor is further modified to improve its stability to changes in affine projection and illumination....
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...For the object recognition problem, Schmid & Mohr [19] also used the Harris corner detector to identify interest points, and then created a local image descriptor at each interest point from an orientation-invariant vector of derivative-of-Gaussian image measurements....
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..., Schmid & Mohr [19]) has shown that efficient recognition can often be achieved by using local image descriptors sampled at a large number of repeatable locations....
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...However, recent research on the use of dense local features (e.g., Schmid & Mohr [19]) has shown that efficient recognition can often be achieved by using local image descriptors sampled at a large number of repeatable locations....
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1,574 citations
"Object recognition from local scale..." refers methods in this paper
...[23] used the Harris corner detector to identify feature locations for epipolar alignment of images taken from differing viewpoints....
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