Object Description Based on Spatial Relations between Level-Sets

Object recognition methods usually rely on either structural or statistical description. These methods aim at describing different types of information such as the outer contour, the inner structure or texture effects. Comparing two objects then comes down to averaging different data representations...

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Published in2012 International Conference on Digital Image Computing: Techniques and Applications pp. 1 - 7
Main Authors Garnier, M., Hurtut, T., Wendling, L.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2012
Subjects
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ISBN9781467321808
146732180X
DOI10.1109/DICTA.2012.6411730

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Abstract Object recognition methods usually rely on either structural or statistical description. These methods aim at describing different types of information such as the outer contour, the inner structure or texture effects. Comparing two objects then comes down to averaging different data representations which may be a tricky issue. In this paper, we introduce an object descriptor based on the spatial relations that structures object content. This descriptor integrates in a single homogeneous representation both shape information and relative spatial information about the object under consideration. We use this description in the context of image retrieval and show results on a butterfly image database compared with both GFD and SIFT descriptors. These results show that our method is more efficient to distinguish the objects where the spatial organization is a discriminative feature.
AbstractList Object recognition methods usually rely on either structural or statistical description. These methods aim at describing different types of information such as the outer contour, the inner structure or texture effects. Comparing two objects then comes down to averaging different data representations which may be a tricky issue. In this paper, we introduce an object descriptor based on the spatial relations that structures object content. This descriptor integrates in a single homogeneous representation both shape information and relative spatial information about the object under consideration. We use this description in the context of image retrieval and show results on a butterfly image database compared with both GFD and SIFT descriptors. These results show that our method is more efficient to distinguish the objects where the spatial organization is a discriminative feature.
Author Wendling, L.
Hurtut, T.
Garnier, M.
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  surname: Wendling
  fullname: Wendling, L.
  email: Laurent.Wendling@parisdescartes.fr
  organization: LIPADE, Univ. Paris Descartes, Paris, France
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Snippet Object recognition methods usually rely on either structural or statistical description. These methods aim at describing different types of information such as...
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SubjectTerms Force
Histograms
Level set
Object recognition
Robustness
Shape
Title Object Description Based on Spatial Relations between Level-Sets
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