Distinctive Image Features from Scale-Invariant Keypoints
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Additional excerpts
...While scaleinvariant feature transform (SIFT) [27] and speeded up robust features (SURF) [20] are the features of choice, they are not suitable for real-time implementations (15 Hz or greater)....
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...While SIFT [24] and SURF [17] are the features of choice, they are not suitable for real-time implementations (15 Hz or greate r)....
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620 citations
Cites background from "Distinctive Image Features from Sca..."
...with three of the most widespread scale-invariant IPs: Harris-Laplace [21], LoG [19], and DoG [19]....
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...All IPs are described by the extremely popular 128-dimensional SIFT [19]....
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References
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"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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