Presentation 2014-12-19
Count The Number of Same Shape Objects in A Snap Image using SOM
Yuriko TSUNODA, Kouichiro HAYASHI, Hideaki KAWANO, Hiroshi MAEDA,
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Abstract(in English) Currently, autonomous robots are studied in various fields. To robot act autonomously, it is important to recognize the object number from the surrounding environment. Thus, simple and easy way to enumerate the objects automatically has been expected. In this study we propose a method to recognize the number of objects in image. To achieve robustness against spatial transformation, such as translation, rotation, and scaling, scale-invariant feature transform (SIFT) is employed as a feature. In order to count the number of objects from feature, we use cluster analysis by SOM. To show the effectiveness, the proposed method is applied to an image containing everyday objects.
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Keyword(in English) self-organizing feature map / cluster analysis / SIFT features / object counting
Paper # SIS2014-84
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Committee SIS
Conference Date 2014/12/11(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Count The Number of Same Shape Objects in A Snap Image using SOM
Sub Title (in English)
Keyword(1) self-organizing feature map
Keyword(2) cluster analysis
Keyword(3) SIFT features
Keyword(4) object counting
1st Author's Name Yuriko TSUNODA
1st Author's Affiliation Kyushu Institute of Technology()
2nd Author's Name Kouichiro HAYASHI
2nd Author's Affiliation Kyushu Institute of Technology
3rd Author's Name Hideaki KAWANO
3rd Author's Affiliation Kyushu Institute of Technology
4th Author's Name Hiroshi MAEDA
4th Author's Affiliation Kyushu Institute of Technology
Date 2014-12-19
Paper # SIS2014-84
Volume (vol) vol.114
Number (no) 370
Page pp.pp.-
#Pages 4
Date of Issue