A sparse texture representation using local affine regions

Urbana University · Institute of Electrical and Electronics Engineers · +3 more institutions

PubMed
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Abstract

This paper introduces a texture representation suitable for recognizing images of textured surfaces under a wide range of transformations, including viewpoint changes and nonrigid deformations. At the feature extraction stage, a sparse set of affine Harris and Laplacian regions is found in the image. Each of these regions can be thought of as a texture element having a characteristic elliptic shape and a distinctive appearance pattern. This pattern is captured in an affine-invariant fashion via a process of shape normalization followed by the computation of two novel descriptors, the spin image and the RIFT descriptor. When affine invariance is not required, the original elliptical shape servee as an…

Citation impact

1,125
total citations
FWCI
25.42
Percentile
100%
References
56
Citations per year

Authors

3

Topics & keywords

Keywords
  • Affine transformation
  • Artificial intelligence
  • Discriminative model
  • Pattern recognition (psychology)
  • Image texture
  • Computer science
  • Feature extraction
  • Computer vision
UN Sustainable Development Goals
  • Reduced inequalities
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