Presentation 2018-01-18
Comparison between saliency maps using top-down and bottom-up factors
Shoichi Adachi, Aya Shiraiwa, Shigang Li,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) It is known that humans possess the ability to analyze complex scenes in real time. Based on this ability, saliency maps have been proposed that visualize the saliency of such scenes. In recent years, research using saliency maps has been actively conducted. In this study, we analyze the attention of humans while driving a car with a saliency map, using bottom-up factors for differentiating among colors and shapes, and top-down factors determined by deep learning. Furthermore, both subjective and objective evaluations are conducted to compare and evaluate the saliency maps in terms of each factor for attention analysis.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Saliency Map / Deep Learning / Gaze measurement
Paper # PRMU2017-120,MVE2017-41
Date of Issue 2018-01-11 (PRMU, MVE)

Conference Information
Committee PRMU / MVE / IPSJ-CVIM
Conference Date 2018/1/18(2days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Shinichi Sato(NII) / Yoshinari Kameda(Univ. of Tsukuba)
Vice Chair Hironobu Fujiyoshi(Chubu Univ.) / Yoshihisa Ijiri(Omron) / Kenji Mase(Nagoya Univ.)
Secretary Hironobu Fujiyoshi(AIST) / Yoshihisa Ijiri(NAIST) / Kenji Mase(Kyoto Univ.) / (NTT)
Assistant Masato Ishii(NEC) / Yusuke Sugano(Osaka Univ.) / Takatsugu Hirayama(Nagoya Univ.) / Ryosuke Aoki(NTT)

Paper Information
Registration To Technical Committee on Pattern Recognition and Media Understanding / Technical Committee on Media Experience and Virtual Environment / Special Interest Group on Computer Vision and Image Media
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Comparison between saliency maps using top-down and bottom-up factors
Sub Title (in English)
Keyword(1) Saliency Map
Keyword(2) Deep Learning
Keyword(3) Gaze measurement
1st Author's Name Shoichi Adachi
1st Author's Affiliation Tottori University(Tottori Univ.)
2nd Author's Name Aya Shiraiwa
2nd Author's Affiliation Tottori University(Tottori Univ.)
3rd Author's Name Shigang Li
3rd Author's Affiliation Hirosima City University(Hirosima City Univ.)
Date 2018-01-18
Paper # PRMU2017-120,MVE2017-41
Volume (vol) vol.117
Number (no) PRMU-391,MVE-392
Page pp.pp.75-80(PRMU), pp.75-80(MVE),
#Pages 6
Date of Issue 2018-01-11 (PRMU, MVE)