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On SIFTs and their scales
TLDR
This paper turns to the overwhelming majority of pixels, those where stable scales are not found by standard techniques, and shows that representing each pixel as a set of SIFTs, extracted at multiple scales, allows for far better matches than single-scale descriptors, but at a computational price. Expand
SIFTing Through Scales
TLDR
This paper turns to the overwhelming majority of pixels, those where stable scales are not found by standard techniques, and shows that representing each pixel as a set of SIFTs, extracted at multiple scales, allows for far better matches than single-scale descriptors, but at a computational price. Expand
On Sifts and Their Scales Lihi Zelnik-manor Technion
Scale invariant feature detectors often find stable scales in only a few image pixels. Consequently, methods for feature matching typically choose one of two extreme options: matching a sparse set ofExpand
Dense, Scale-Less Descriptors
TLDR
This chapter discusses alternative representations designed to capture multiscale appearance, even in image regions where existing methods for scale selection are not effective, and demonstrates how the use of the SLS descriptor can act as an alternative to existing, single scale representations, allowing for accurate dense correspondences between images with scale-varying content. Expand