Object recognition from local scale-invariant features
Citations
129 citations
Cites methods from "Object recognition from local scale..."
...A scale invariant feature transform (SIFT) is then used to track the object under different image magnifications and rotations [126, 127]....
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128 citations
128 citations
Cites methods from "Object recognition from local scale..."
...Specifically, we use 12 filters with orientations 0◦, 30◦, 60◦ and 90◦ and frequencies 0.0, 0.1 and 0.4....
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128 citations
Cites methods from "Object recognition from local scale..."
...As the first step, the Scale Invariant Feature Transform (SIFT) detector and descriptor are used to find keypoint locations and provide a local descriptor for each keypoint (Lowe, 1999)....
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128 citations
Cites methods from "Object recognition from local scale..."
...We have tested three different features respectively descriptors: Shi-Tomasi features and representing a patch by a view set [22,33], the Maximally Stable Extremal Regions (MSER) in combination with the Local Affine Frames (LAF) as presented in [25], and the SIFT features [18]....
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...In the following, we present our system for the recognition and localization of textured objects, which builds on top of the approach proposed in [18]....
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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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