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Paper Abstract and Keywords
Presentation 2020-02-27 14:40
A Note on Eye Gaze Based User-specific Interest Estimation for Images -- Estimation Performance Improvement Based on sMVCCA including Ordinal Label Dequantization --
Masanao Matsumoto (Hokkaido Univ.), Naoki Saito (NIT, Kushiro College), Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) This paper presents supervised multiview canonical correlation analysis via ordinal label dequantization (sMVCCA-OLD) for image interest estimation.
sMVCCA-OLD is a new supervised CCA method realizing accurate integration of features including low-dimensional ordinal label features by introducing label dequantization scheme to sMVCCA.
In sMVCCA, there is a possibility of missing information that is necessary for image interest estimation since the dimensions of integrated features is limited by the number of classes.
sMVCCA-OLD can solve this problem by increasing the dimension of the ordinal label information with the estimation of the canonical correlation between multiview features.
From experimental results obtained by applying our method to the image interest level estimation, it is confirmed that accuracy improvement using sMVCCA-OLD becomes feasible compared to recent CCA-based methods.
Keyword (in Japanese) (See Japanese page) 
(in English) eye gaze data / canonical correlation analysis / ordinal label dequantization / interest level estimation / / / /  
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Conference Information
Committee ITE-HI IE ITS ITE-MMS ITE-ME ITE-AIT  
Conference Date 2020-02-27 - 2020-02-28 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Image Processing, etc. 
Paper Information
Registration To ITE-ME 
Conference Code 2020-02-HI-IE-ITS-MMS-ME-AIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Note on Eye Gaze Based User-specific Interest Estimation for Images 
Sub Title (in English) Estimation Performance Improvement Based on sMVCCA including Ordinal Label Dequantization 
Keyword(1) eye gaze data  
Keyword(2) canonical correlation analysis  
Keyword(3) ordinal label dequantization  
Keyword(4) interest level estimation  
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1st Author's Name Masanao Matsumoto  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Naoki Saito  
2nd Author's Affiliation National Institute of Technology, Kushiro College (NIT, Kushiro College)
3rd Author's Name Takahiro Ogawa  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
4th Author's Name Miki Haseyama  
4th Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker Author-1 
Date Time 2020-02-27 14:40:00 
Presentation Time 15 minutes 
Registration for ITE-ME 
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Volume (vol) vol.119 
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