A sparse texture representation using local affine regions
Urbana University · Institute of Electrical and Electronics Engineers · +3 more institutions
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
- FWCI
- 25.42
- Percentile
- 100%
- References
- 56
Authors
3- SLSvetlana LazebnikCorresponding
Urbana University
- CSC. Schmid
Institute of Electrical and Electronics Engineers, Institut national de recherche en informatique et en automatique, Centre Inria de l'Université Grenoble Alpes
- JPJean Ponce
University of Illinois Urbana-Champaign, Institute of Electrical and Electronics Engineers
Topics & keywords
- Affine transformation
- Artificial intelligence
- Discriminative model
- Pattern recognition (psychology)
- Image texture
- Computer science
- Feature extraction
- Computer vision
- Reduced inequalities