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A Sparse Texture Representation Using Local Affine Regions
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2005.151August 2005 (vol. 27 no. 8) pp. 1265-1278
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Svetlana Lazebnik, Cordelia Schmid, Jean Ponce, "A Sparse Texture Representation Using Local Affine Regions," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 8, pp. 1265-1278, August, 2005.
 
 
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@article{ 10.1109/TPAMI.2005.151,
author = {Svetlana Lazebnik and Cordelia Schmid and Jean Ponce},
title = {A Sparse Texture Representation Using Local Affine Regions},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {27},
number = {8},
issn = {0162-8828},
year = {2005},
pages = {1265-1278},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2005.151},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - A Sparse Texture Representation Using Local Affine Regions
IS - 8
SN - 0162-8828
SP1265
EP1278
EPD - 1265-1278
A1 - Svetlana Lazebnik,
A1 - Cordelia Schmid,
A1 - Jean Ponce,
PY - 2005
KW - Index Terms- Image processing and computer vision
KW - feature measurement
KW - texture
KW - pattern recognition.
VL - 27
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
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 serves as an additional discriminative feature for texture recognition. The proposed approach is evaluated in retrieval and classification tasks using the entire Brodatz database and a publicly available collection of 1,000 photographs of textured surfaces taken from different viewpoints.

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Index Terms:
Index Terms- Image processing and computer vision, feature measurement, texture, pattern recognition.
Citation:
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce, "A Sparse Texture Representation Using Local Affine Regions," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 8, pp. 1265-1278, Aug. 2005, doi:10.1109/TPAMI.2005.151
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