Locally Affine Invariant Descriptors for Shape Matching and Retrieval

This work proposes novel locally affine invariant descriptors for shape representation. The descriptors are theoretically simple and solid, derived from the matrix theories. They can be used for matching and retrieval of shapes under affine transformation, articulated motion or nonrigid deformation....

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Bibliographic Details
Published in:IEEE signal processing letters 2010-09, Vol.17 (9), p.803-806
Main Authors: Wang, Zhaozhong, Liang, Min
Format: Article
Language:English
Subjects:
Affine invariance
Anisotropic magnetoresistance
Diffusion processes
Image databases
Image processing
Image retrieval
Invariants
Matching
Matrix theory
Pattern matching
Pattern recognition
Representations
Retrieval
Running
shape descriptor
shape matching
Shape measurement
shape retrieval
Shearing
Solids
State of the art
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Summary:This work proposes novel locally affine invariant descriptors for shape representation. The descriptors are theoretically simple and solid, derived from the matrix theories. They can be used for matching and retrieval of shapes under affine transformation, articulated motion or nonrigid deformation. Comparisons of the work with the state-of-the-art shape descriptors are performed based on synthetic and some well-known databases. The experiments validate that the proposed descriptors achieve higher retrieval accuracy and have faster running speed than most of other approaches.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2010.2057506