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ACCV
2009
Springer

Image Classification Using Probability Higher-Order Local Auto-Correlations

9 years 1 months ago
Image Classification Using Probability Higher-Order Local Auto-Correlations
Abstract. In this paper, we propose a novel method for generic object recognition by using higher-order local auto-correlations on probability images. The proposed method is an extension of bag-of-features approach to posterior probability images. Standard bag-of-features is approximately thought as sum of posterior probabilities on probability images, and spatial co-occurrences of posterior probability are not utilized. Thus, its descriptive ability is limited. However, using local auto-correlations of probability images, the proposed method extracts richer information than the standard bag-of-features. Experimental results show the proposed method is enable to have higher classification performances than the standard bag-of-features.
Tetsu Matsukawa, Takio Kurita
Added 29 Sep 2010
Updated 29 Sep 2010
Type Conference
Year 2009
Where ACCV
Authors Tetsu Matsukawa, Takio Kurita
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