Image categorization through optimum path forest and visual words
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Data
2011-12-01
Autores
Papa, João Paulo [UNESP]
Rocha, Anderson
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Resumo
Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE.
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Image Categorization, Local Interest Points, Optimum Path Forest, Visual Dictionaries, Global feature, Interest points, Visual word, Forestry, Image processing, Imaging systems, Image Analysis, Problem Solving
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Proceedings - International Conference on Image Processing, ICIP, p. 3525-3528.