Distinctive Image Features from Scale-Invariant Keypoints
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450 citations
Cites methods from "Distinctive Image Features from Sca..."
...Walther [2006] combines an attention system with an object recognizer based on SIFT features [Lowe 2004] and shows that the recognition results are improved by the attentional front-end (see Figure 12(b))....
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...A common approach is the SIFT descriptor (scale invariant feature transform), which captures the gradient magnitude in the surrounding of a region [Lowe 2004]....
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...Walther [2006] combines an attention system with an object recognizer based on SIFT features [Lowe 2004] and shows that the recognition results are improved by the attentional front-end (see Figure 12(b))....
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...A common approach is the SIFT descriptor (scale invariant feature transform), which captures the gradient magnitude in the surrounding of a region [Lowe 2004]....
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449 citations
446 citations
445 citations
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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