Distinctive Image Features from Scale-Invariant Keypoints
Citations
356 citations
Cites methods from "Distinctive Image Features from Sca..."
...However, the scale and rotation invariance of the SIFT keys, which increases the processing requirements, is not necessary in the EDL scenario considered here....
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...SIFT keypoints can be reliably matched between images under large scale and in-plane orientation changes....
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...One image-feature detection algorithm that was considered during our system’s design is the scale-invariant feature transform (SIFT) [7]....
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...One image feature detection algorithm that was considered during our system’s design is the scale invariant feature transform (SIFT) [7]....
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356 citations
356 citations
355 citations
355 citations
Additional excerpts
...The SIFT descriptor [38] has emerged as one of the most reliable descriptors....
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References
16,989 citations
"Distinctive Image Features from Sca..." refers background or methods in this paper
...The initial implementation of this approach (Lowe, 1999) simply located keypoints at the location and scale of the central sample point....
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...Earlier work by the author (Lowe, 1999) extended the local feature approach to achieve scale invariance....
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...More details on applications of these features to recognition are available in other pape rs (Lowe, 1999; Lowe, 2001; Se, Lowe and Little, 2002)....
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...To efficiently detect stable keypoint locations in scale space, we have proposed (Lowe, 1999) using scalespace extrema in the difference-of-Gaussian function convolved with the image, D(x, y, σ ), which can be computed from the difference of two nearby scales separated by a constant multiplicative…...
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...More details on applications of these features to recognition are available in other papers (Lowe, 1999, 2001; Se et al., 2002)....
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"Distinctive Image Features from Sca..." refers background in this paper
...A more general solution would be to solve for the fundamental matrix (Luong and Faugeras, 1996; Hartley and Zisserman, 2000)....
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13,993 citations
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