iat_dense_sift

[SIFTIMAGE, GRIDX,GRIDY] = iat_dense_sift(IMAGE, PS, GSPACING)

iat_dense_sift creates SIFTIMAGE from IMAGE when the pixels of latter are replaced by SIFT descriptors [1],[2]. SIFTIMAGE is defined on the meshgrid [GRIDX, GRIDY], which results from IMAGE’s sampling with GSPACING factor (after ignoring PS/2 rows and columns from all image sides)

Input arguments:

IMAGE The input image
PS The width (=height) of the square patch that is described by SIFT vectors
GRIDSPACING the sampling factor of IMAGE’s grid that defines the resolution of SIFTIMAGE

[SIFTIMAGE, GRIDX,GRIDY] = iat_dense_sift(IMAGE, PS, GSPACING, ‘PARAM1′, PARAM1VALUE,…)

The above syntax allows the user to define his own parameters. There parameters are:

‘numAngles’ The quantization step (angle) for gradient orientation (default: 8)
‘numBins’ The number of spatial bins in each dimension (default: 4).The size of each SIFT descriptor is numAngles*numBins*numBins
‘alpha’ The attenuation of angles; it must be odd number (default: 9)
‘sigma’ The scale of gaussian kernel for computing DOG (default: 1).When sigma is scalar, the size of kernel is (4*ceil(sigma)+1)X(4*ceil(sigma)+1). When sigma is a 2-element vector, i.e. [sigmaX, sigmaY], the size of the kernel is (4*ceil(sigmaY)+1)X(4*ceil(sigmaX)+1)

 

Output arguments:

SIFTIMAGE The output SIFT-image
GRIDX,GRIDY The meshgrid that defines the support area of SIFTIMAGE

 

References:

[1] C. Liu, J. Yuen, A. Torralba: SIFT Flow: Dense Correspondence across Scenes and its Applications, IEEE Trans. on PAMI, vol. 33, no. 5, 2011

[2] D.G. Lowe, Distinctive image features from scale-invariant keypoints, Int. Journal on Computer Vision, vol. 60, no. 2, 2004

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