Presentation 2021-10-22
A saliency estimation model for drivers' egocentric vision movies considering self-motion velocity
Yuya Homma, Masashi Fujita, Takeshi Kohama,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) In order to predict where a driver’s attention should be directed during driving, Kodama et al. have developed a saliency estimation model for self-motion images that take into account the receptive field characteristics of the early visual system and higher-order motion selection mechanisms. However, Kodama et al.’s model has some problems, such as reduced prediction accuracy when driving at low speeds, and the response of the receptive field model to extract features in dark areas remains an issue. In this study, to construct a mathematical model for a more accurate prediction of driver’s gaze while driving a car, we added the process of dynamically changing the frame-interval when calculating motion vectors and modified the on-center and off-center antagonistic receptive field responses to the Kodama et al.’s model. The results suggest that the moving-NSS (Moving-Normalized Scanpath Saliency) score, which indicates the prediction accuracy of the attentional area, improved for all subjects in the scenes with low-speed driving and the scenes with many dark features.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Driver’s egocentric vision / Attention prediction / Saliency map / Motion detection / Early visual system receptive fields
Paper # HIP2021-44
Date of Issue 2021-10-14 (HIP)

Conference Information
Committee HIP
Conference Date 2021/10/21(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Shuichi Sakamoto(Tohoku Univ.)
Vice Chair Yuji Wada(Ritsumeikan Univ.) / Sachiko Kiyokawa(Nagoya Univ.)
Secretary Yuji Wada(NTT) / Sachiko Kiyokawa(NICT)
Assistant Yuki Yamada(Kyushu Univ.) / Daisuke Tanaka(Tottori Univ.) / Ippei Negishi(Kanazawa Inst. of Tech.)

Paper Information
Registration To Technical Committee on Human Information Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A saliency estimation model for drivers' egocentric vision movies considering self-motion velocity
Sub Title (in English)
Keyword(1) Driver’s egocentric vision
Keyword(2) Attention prediction
Keyword(3) Saliency map
Keyword(4) Motion detection
Keyword(5) Early visual system receptive fields
1st Author's Name Yuya Homma
1st Author's Affiliation Kindai University(Kindai Univ.)
2nd Author's Name Masashi Fujita
2nd Author's Affiliation Kindai University(Kindai Univ.)
3rd Author's Name Takeshi Kohama
3rd Author's Affiliation Kindai University(Kindai Univ.)
Date 2021-10-22
Paper # HIP2021-44
Volume (vol) vol.121
Number (no) HIP-211
Page pp.pp.75-80(HIP),
#Pages 6
Date of Issue 2021-10-14 (HIP)