Distinctive Image Features from Scale-Invariant Keypoints
Citations
138 citations
Cites background or methods from "Distinctive Image Features from Sca..."
...Lowe [17] proposed a scale invariant feature transform (SIFT), which was originally applied to perform reliable matching between different views of an object or scene....
[...]
...against visual descriptor variances, separate experiments were carried out with SIFT [17], LBP (Local Binary Pattern) [29,30], and WHGO (Weighted Histograms of Gradient Orientation) [31] descriptors for the OT, FP, and LS data sets....
[...]
...The bag-offeatures model samples an image efficiently with various local interest point detectors [16,17] or dense regions [11,15], and describes it with local descriptors [17,18]....
[...]
...This approach constructs multiple resolution images and extracts SIFT features [17] for all resolution images with dense regions....
[...]
138 citations
138 citations
137 citations
Cites background from "Distinctive Image Features from Sca..."
...and the second-smallest dissimilarity measure for that jigsaw piece’s edge (akin to SIFT feature matching [15])....
[...]
137 citations
Cites background from "Distinctive Image Features from Sca..."
...Fixation points amount to features in the scene and the recent literature on features comes in handy[18, 22]....
[...]
References
46,906 citations
16,989 citations
13,993 citations
7,057 citations
3,422 citations