Title :
Efficient object matching using affine-invariant deformable contour
Author :
Xue, Zhong ; Li, Stan Z. ; Teoh, Eam Khwang
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Inst., Singapore
Abstract :
An affine-invariant deformable contour model for object matching, called affine-invariant eigensnake (AI-ES), is presented in the Bayesian framework. In AI-ES, the prior distribution of object shapes is estimated and utilized to constrain the prototype contour, which is dynamically adjustable in the matching process. Also, an affine-invariant internal energy is presented to define the global and local shape deformation of the contours between the shape domain and the image domain. Experiments on real object matching show that the proposed method is more robust and insensitive to the positions, viewpoints, and large deformations of object shapes, than the active shape model (ASM) and the AI-snake model
Keywords :
Bayes methods; image matching; object recognition; AI-ES; AI-snake model; ASM; Bayesian framework; active shape model; affine-invariant deformable contour; affine-invariant eigensnake; affine-invariant internal energy; efficient object matching; global shape deformation; insensitivity; local shape deformation; object shape distribution; prototype contour; real object matching; robustness; Active shape model; Artificial intelligence; Bayesian methods; Deformable models; Parametric statistics; Principal component analysis; Prototypes; Robustness; Shearing;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.905477