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Paper Abstract and Keywords
Presentation 2019-05-17 10:00
An investigation of the most "kawaii" shape using preferential Bayesian optimization
Masashi Komoei (OECU)
Abstract (in Japanese) (See Japanese page) 
(in English) This study aims to explore a psychophysical latent function of perceived “Kawaii” (cuteness) against multidimensional shape parameters using a Bayesian optimization (BO) methodology. BO is an effective approach to sequentially optimize the black-box function in cases where the cost for evaluations are high. In standard BO applications (e.g., parameter tuning for machine learning), it is possible to query objective functions directly. However, humans are better at evaluating differences rather than absolute magnitudes. Thus, instead of standard BO, we performed preferential BO, which enables the estimation of the latent function through two-alternative forced choice task. To generate the pairs of stimulus images for the comparison, we used the Expected Improvement (EI) acquisition function. Each contour shape stimulus was created by elliptic Fourier descriptors (EFDs) based on six parameters (up to the third harmonic) calculated by Gaussian process regression and EI. Fourteen participants provided their preferences for the pairs of contour images in seventy trials. Based on the results, we estimated the most “kawaii” shape and the least “kawaii” shape on average. The most kawaii shape was found to be round and to have two protrusions on the top.
Keyword (in Japanese) (See Japanese page) 
(in English) Bayesian Optimization / Kawaii / Shape / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 38, HCS2019-15, pp. 109-112, May 2019.
Paper # HCS2019-15 
Date of Issue 2019-05-09 (HCS, HIP) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380

Conference Information
Committee HCS HIP HI-SIGCE  
Conference Date 2019-05-16 - 2019-05-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Industry Support Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To HCS 
Conference Code 2019-05-HCS-HIP-SIGCE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) An investigation of the most "kawaii" shape using preferential Bayesian optimization 
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Keyword(1) Bayesian Optimization  
Keyword(2) Kawaii  
Keyword(3) Shape  
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1st Author's Name Masashi Komoei  
1st Author's Affiliation Osaka Electro-Communication University (OECU)
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Speaker
Date Time 2019-05-17 10:00:00 
Presentation Time 25 
Registration for HCS 
Paper # IEICE-HCS2019-15,IEICE-HIP2019-15 
Volume (vol) IEICE-119 
Number (no) no.38(HCS), no.39(HIP) 
Page pp.109-112 
#Pages IEICE-4 
Date of Issue IEICE-HCS-2019-05-09,IEICE-HIP-2019-05-09 


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