Distinctive Image Features from Scale-Invariant Keypoints
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Cites background from "Distinctive Image Features from Sca..."
...For example, sparse SIFT descriptors [38] are extracted on interest points, and the DCNN may only be evaluated on a few locations....
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...Furthermore, the re are also many unavoidable false matches that are more numerous than those usually output by the SIFT on standard perspectiv e images (about 20-30% according to [16]) because of the large distortion introduced by the mirror....
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...The first one is a feature-based tracker that uses SIFT features and a RANSAC-based outlier removal to track the key points that most likely belong to the ground plane....
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...Our key points are Scale Invariant Features (SIFT) [16], as they proved to work well also with omnidirectional pictures....
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...1) Let A be the set of all image pairs output by SIFT from two consecutive frames....
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...The material includes two video files, where description is as follows: The first video, SIFT&path.wmv, contains two video sequences; a video of the image dataset with superimposed SIFT features and a video of the trajectory estimated using the visual odometry algorithm described in the paper....
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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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...A more general solution would be to solve for the fundamental matrix (Luong and Faugeras, 1996; Hartley and Zisserman, 2000)....
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