Object recognition from local scale-invariant features
Citations
1,608 citations
Cites background or methods from "Object recognition from local scale..."
...A uniform Gaussian scale-space is often used to deal with scale changes [3, 7, 10, 11]....
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...Lowe [10] proposes an efficient algorithm for recognition based on local extrema of difference-of-Gaussian filters in scale-space....
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...Scale invariant interest points detectors have been presented previously [10, 11]....
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1,607 citations
1,582 citations
Cites background from "Object recognition from local scale..."
...Local feature schemes consist of a region-of-interest detector combined with a descriptor of the local region, SIFT (Lowe 1999) being a popular example....
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...Silpa-Anan and Hartley (2004, 2005) describe a similar system which employs SIFT features....
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1,566 citations
Cites methods from "Object recognition from local scale..."
...Given an image `, the Fisher Vector (FV) formulation of [26] starts by extracting local SIFT [20] descriptors {d1, ....
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...The first one is the use of the SIFT descriptors, originally developed for object matching [20], that are more distinctive that local descriptors popular in texture analysis such as filter banks [13, 19, 36], local intensity patterns [23], and patches [35]....
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1,508 citations
Cites methods from "Object recognition from local scale..."
...Another advantage of using 2D representations is that we can leverage (i) advances in image descriptors [22, 26] and (ii) massive image databases (such as ImageNet [9]) to pre-train our CNN architectures....
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...[30] proposed using Fisher vectors [26] on SIFT features [22] for representing human sketches of shapes....
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References
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1,756 citations
"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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