Object recognition from local scale-invariant features
Citations
694 citations
Cites methods from "Object recognition from local scale..."
...Local Scale-Invariant Features [33] are a powerful tool used in various computer vision tasks including recognition [33] and scene alignment [32]....
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...In particular, some promising trackers [12, 38, 41] have been proposed to model the object appearance based on Local Scale-Invariant Features (i.e., keypoints)....
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690 citations
Cites methods from "Object recognition from local scale..."
...As a fast search, we use spatial histogram matching of quantized SIFT [14,15]....
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...In the SIFT flow, a SIFT descriptor [14] is extracted at each pixel to characterize local image structures and encode contextual information....
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...First, we assume SIFT descriptors [14] extracted at each pixel location (instead of raw pixel values) are constant with respect to the pixel displacement field....
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687 citations
Cites background from "Object recognition from local scale..."
...Finally, conclusions will be presented in Section V....
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686 citations
Cites methods from "Object recognition from local scale..."
...Many place recognition techniques rely on feature-finding algorithms such as SIFT [9] and SURF [10] which, despite their impressive rotation and scale invariant properties, are inherently unsuitable when dealing with extreme perceptual M.J. Milford and G.F. Wyeth are with the School of Electrical Engineering and Computer Science at the Queensland University of Technology, Brisbane, Australia, michael.milford@qut.edu.au....
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...In that approach, 128D vectors of SIFT descriptors were used to perform loop closure, combined with additional algorithms to address visual ambiguity caused by repetitive foliage or architecture features....
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...Many place recognition techniques rely on feature-finding algorithms such as SIFT [9] and SURF [10] which, despite their impressive rotation and scale invariant properties, are inherently unsuitable when dealing with extreme perceptual...
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683 citations
Cites methods from "Object recognition from local scale..."
...Two descriptors were investigated: (i) the SIFT descriptor [11] computes a histogram of gradient orientation on a coarse spatial grid, aiming to emphasize strong edge features and give some robustness to image deformation....
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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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