Presentation 2010-09-22
A Study on Performance Improvement of Generic Object Recognition by Object Extraction
Tetsuya FUJIKAWA, Jiro KATTO,
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Abstract(in English) In Bag-of-Keypoints method used in generic object recognition, we ordinarily derive SIFT features over the whole regions of images. However, in some categories, information of background regions is not effective for recognition. Therefore, in this paper, we investigate the effect of object extraction on the recognition rate of Bag-of-Keypoints. Firstly, by using ground truth data of foreground objects, we found that classification rate can be improved by 7% in average and region extraction is effective for some categories but not for other categories. Secondly, we propose a method to extract object regions automatically by using visual attention model prior to Bag-of-Keypoints. Unfortunately, this method shows only 1.5% improvement mainly due to categories which need background regions. Finally, we propose an adaptive method which selects foreground regions or whole image for SIFT feature description according to categories. Experimental results show that above 7% improvement is furthermore expected against other methods described above.
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Keyword(in English) Generic Object Recognition / Bag-of-Keypoints / Object Extraction / Visual Attention Model
Paper # LOIS2010-28,IE2010-70
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Committee LOIS
Conference Date 2010/9/14(1days)
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Registration To Life Intelligence and Office Information Systems (LOIS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study on Performance Improvement of Generic Object Recognition by Object Extraction
Sub Title (in English)
Keyword(1) Generic Object Recognition
Keyword(2) Bag-of-Keypoints
Keyword(3) Object Extraction
Keyword(4) Visual Attention Model
1st Author's Name Tetsuya FUJIKAWA
1st Author's Affiliation Graduate School of Fundamental Science and Engineering, Waseda University()
2nd Author's Name Jiro KATTO
2nd Author's Affiliation Graduate School of Fundamental Science and Engineering, Waseda University
Date 2010-09-22
Paper # LOIS2010-28,IE2010-70
Volume (vol) vol.110
Number (no) 207
Page pp.pp.-
#Pages 6
Date of Issue