Distinctive Image Features from Scale-Invariant Keypoints
Citations
86 citations
Cites methods from "Distinctive Image Features from Sca..."
...The originality of the work consisted in the usage of Gauss-Laguerre Harmonic Functions (GL-CHFs) instead of traditional SIFT[12] and SURF[13] descriptors....
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...The authors construct the united data representation for each patient: F = [X1; X2; Z1; Z2] ∈ R4d×n and calculate SIFT descriptors....
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...tions (GL-CHFs) instead of traditional SIFT[12] and SURF[13] descriptors....
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...As an alternative to heavy volumetric methods, feature-based approaches were applied in the problem of AD detection using domain knowledge both on the ROI biomarkers and on the nature of the signal in sMRI and DTI modalities which is blurry and cannot be sufficiently well described by conventional differential descriptors such as SIFT[12] and SURF[13]....
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...ferential descriptors such as SIFT[12] and SURF[13]....
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85 citations
85 citations
Cites methods from "Distinctive Image Features from Sca..."
...We use the Scale Invariant Feature Tracking (SIFT) descriptor to estimate the 3D position for the target object from the gripper stereo camera [25]....
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85 citations
Cites methods from "Distinctive Image Features from Sca..."
...In particular, we use hessian affine features and the SIFT descriptor [12]....
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85 citations
Cites background or methods from "Distinctive Image Features from Sca..."
...The scale-invariant feature transform (SIFT) operator (Lowe, 1999, 2004) can transform image data into scale-invariant coordinates relative to local features....
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...According to Lowe (1999, 2004), the major stages of computation used to generate a set of image features are: scale-space extrema [sic] detection, keypoint localisation, orientation assignment and keypoint descriptor....
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References
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