Object recognition from local scale-invariant features
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120Â citations
Cites methods from "Object recognition from local scale..."
...The conjugate points of a stereo pair of images are extracted by the scale-invariant feature transform (SIFT) operator [38] and the outliers are identified and eliminated by the RANdom SAmple Consensus (RANSAC) approach [39]....
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120Â citations
120Â citations
Cites background or methods from "Object recognition from local scale..."
...Therefore, it is more difficult to preserve image features, which TABLE II INFLUENCE OF THE ARTIFICIAL GENERATED TEMPLATES ON THE MATCHING ACCURACY AND PRECISION OF NCC [16], SIFT [17], BRISK [18], AND A COMPARISON WITH TWO BASELINE METHODS...
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...The evaluation focuses on one intensity-based, NCC [16], and on two feature-based matching approaches, SIFT [17] and binary robust invariant scalable key (BRISK) [18]....
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...TABLE III INFLUENCE OF LOSS FUNCTION ON THE MATCHING ACCURACY AND PRECISION OF NCC [16], SIFT [17], BRISK [18]...
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...The two feature detectors utilized in this paper are the SIFT [17] and the BRISK [18]....
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119Â citations
References
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1,756Â 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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1,574Â 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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