Presentation 2010-05-14
Scene Image Recognition with Multi Level Resolution Semantic Modeling
Yoshiyuki Tanaka, Atsushi Okamoto, Xian-Hua Han, Xiang Ruan, Yen-Wei Chen,
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Abstract(in English) In this paper, we propose a multi-level resolution semantic modeling for automatic scene recognition. The basic idea of the semantic modeling is to classify local image regions into semantic concept classes such as water, sunset, or sky, and use occurrence frequency of local region's semantic concepts for global image representation. However, how to decide size of the local image regions is a trial problem. The optimized region size would be dynamically changing for different scene or concept types. Therefore, this paper proposed a dynamical region size(Multi-level resolution)of local image regions for semantic concept model, and fusion the probabilities to scene types of several resolutions for final recognition of a scene image. Experimental results show that the recognition rate using our proposed algorithm is much better than that using the conventional semantic modeling method for scene recognition.
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Keyword(in English) Semantic Modeling / multi level resolution / scene recognition
Paper # IE2010-44,PRMU2010-32,MI2010-32
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Committee MI
Conference Date 2010/5/6(1days)
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Registration To Medical Imaging (MI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Scene Image Recognition with Multi Level Resolution Semantic Modeling
Sub Title (in English)
Keyword(1) Semantic Modeling
Keyword(2) multi level resolution
Keyword(3) scene recognition
1st Author's Name Yoshiyuki Tanaka
1st Author's Affiliation Ritsumeikan University()
2nd Author's Name Atsushi Okamoto
2nd Author's Affiliation Ritsumeikan University
3rd Author's Name Xian-Hua Han
3rd Author's Affiliation Ritsumeikan University
4th Author's Name Xiang Ruan
4th Author's Affiliation Omron Corporation
5th Author's Name Yen-Wei Chen
5th Author's Affiliation Ritsumeikan University
Date 2010-05-14
Paper # IE2010-44,PRMU2010-32,MI2010-32
Volume (vol) vol.110
Number (no) 28
Page pp.pp.-
#Pages 6
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