Comput Methods Programs Biomed - Tensor based sparse decomposition of 3D shape for visual detection of mirror symmetry.

Tópicos

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Resumo

This study explores an approach for analysing the mirror (reflective) symmetry of 3D shapes with tensor based sparse decomposition. The approach combines non-negative tensor decomposition and directional texture synthesis, with symmetry information about 3D shapes that is represented by 2D textures synthesised from sparse, decomposed images. This technique requires the center of mass of 3D objects to be at the origin of the coordinate system. The decomposition of 3D shapes and analysis of their symmetry are useful for image compression, pattern recognition, as well as there being an emerging interest in the medical community due to its potential to find morphological changes between healthy and pathological structures. This paper postulates that sparse texture synthesis can be used to describe the decomposed basis images acting as symmetry descriptors for a 3D shape. We apply the theory of non-negative tensor decomposition and sparse texture synthesis, deduce the new representation, and show some application examples.

Resumo Limpo

studi explor approach analys mirror reflect symmetri d shape tensor base spars decomposit approach combin nonneg tensor decomposit direct textur synthesi symmetri inform d shape repres d textur synthesis spars decompos imag techniqu requir center mass d object origin coordin system decomposit d shape analysi symmetri use imag compress pattern recognit well emerg interest medic communiti due potenti find morpholog chang healthi patholog structur paper postul spars textur synthesi can use describ decompos basi imag act symmetri descriptor d shape appli theori nonneg tensor decomposit spars textur synthesi deduc new represent show applic exampl

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