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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 56  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
HIP, HCS
(Joint) [detail]
2023-09-11
15:00
Ehime University of Human Environments Relationship between visual field size and head motion in eyepiece displays
Sumio Yano (Shimane Univ.), Shuichi Ojima (Sojo Univ.) HCS2023-60 HIP2023-50
We examined the relationship between the size of the visual field and head motion by using an eyepiece-type display that... [more] HCS2023-60 HIP2023-50
pp.19-24
NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] 2023-06-29
15:10
Okinawa OIST Conference Center
(Primary: On-site, Secondary: Online)
Selective Inference for DNN-driven Saliency Map
Daiki Miwa (NITech), Vo Nguyen Le Duy (RIKEN), Tomohiro Shiraishi (Nagoya Univ.), Ichiro Takeuchi (Nagoya Univ./RIKEN) NC2023-5 IBISML2023-5
The usefulness of image classification using DNN models has been confirmed in various fields, but the prediction mechani... [more] NC2023-5 IBISML2023-5
pp.30-34
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2023-02-22
11:00
Hokkaido Hokkaido Univ. Discussion and user study of displaying 360-degree video that follows RoI
Yuuki Sawabe (UTokyo), Satoshi Ikehata (NII), Kiyoharu Aizawa (UTokyo) ITS2022-63 IE2022-80
Although 360° video images contain information in all directions, the user's viewing angle is limited, resulting in over... [more] ITS2022-63 IE2022-80
pp.118-123
MBE, MICT, IEE-MBE [detail] 2023-01-17
09:50
Saga   Oral Cytology Based on Representation Learning of Visually Salient Cells
Kazuki Matsuo, Eiji Mitate, Tomoya Sakai (Nagasaki Univ.) MICT2022-44 MBE2022-44
We classify microscopically photographed cells for screening tests to find oral cancer in its early stages. Oral cancer ... [more] MICT2022-44 MBE2022-44
pp.7-12
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] 2022-02-21
15:05
Online Online A Note on Personalized Saliency Prediction Based on User Similarity Considering Object Information in Images
Yuya Moroto, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
This paper presents a personalized saliency map (PSM) prediction method using a small amount of gaze data based on user ... [more]
IE, ITS, ITE-AIT, ITE-ME, ITE-MMS [detail] 2022-02-21
15:50
Online Online Statistical Analysis on Estimation of Laparoscopic Image Region of Interest Including Contrast Enhancement Based on Saliency Map
Norifumi Kawabata (Hokkaido Univ.), Toshiya Nakaguchi (Chiba Univ.) ITS2021-34 IE2021-43
In the medical field such as hospital, there are many chance for medical workers to see medical images visually. Therefo... [more] ITS2021-34 IE2021-43
pp.55-60
HIP 2021-10-22
13:35
Online Online A saliency estimation model for drivers' egocentric vision movies considering self-motion velocity
Yuya Homma, Masashi Fujita, Takeshi Kohama (Kindai Univ.) HIP2021-44
In order to predict where a driver’s attention should be directed during driving, Kodama et al. have developed a salienc... [more] HIP2021-44
pp.75-80
MVE, IMQ, IE, CQ
(Joint) [detail]
2021-03-02
09:20
Online Online Creation of a gazing point database when appreciating a painting and comparison with a saliency map
Yusuke Nosaka (Tokai Univ.), Eriko Ishii (Kagoshima Prefectural College), Yuko Hoshino, Mitsuho Yamada (Tokai Univ.) CQ2020-111
It is said that the painter draw painting in order to lead the gaze of the viewer to the intended subject. We assumed t... [more] CQ2020-111
pp.16-21
HCGSYMPO
(2nd)
2020-12-15
- 2020-12-17
Online Online Effects of contextual saliency on users' attention: VR experimental psychology
Yuki Harada, Ohyama Junji (AIST)
Most studies have measured attentional characteristics in real-world environments where subjects are exposed to exogenou... [more]
IMQ, IE, MVE, CQ
(Joint) [detail]
2019-03-15
10:15
Kagoshima Kagoshima University Person Re-identification with Simultaneous Use of Individual and Group Appearance Features
Shingo Inami (Tokyo Univ. of Science), Daisuke Sugimura (Tsuda Univ.), Takayuki Hamamoto (Tokyo Univ. of Science) IMQ2018-58 IE2018-142 MVE2018-89
In this paper, we propose a method for person re-identification (ReID).
Conventional methods have utilized appearance f... [more]
IMQ2018-58 IE2018-142 MVE2018-89
pp.201-204
SIS 2019-03-07
12:35
Tokyo Tokyo Univ. Science, Katsushika Campus A Proposal of Color Quantization Method Taking Account of Saliency
Yoshiaki Ueda, Seiichi Kojima, Noriaki Suetake, Eiji Uchino (Yamaguchi Univ.) SIS2018-52
One of the most popular limited-color images, graphic interchange format (GIF) image is used in various situations. The ... [more] SIS2018-52
pp.81-84
HIP 2018-08-03
09:25
Tokyo Tokyo Woman's Christian University A Study of Presenting Information Based on Human Visual Characteristics Using Eye Tracking and Saliency Map
Yusei Harigaya, Susumu Shirayama (Univ. of Tokyo) HIP2018-50
Researchers have been trying to assist human work by presenting visual information in recent years. However, inappropria... [more] HIP2018-50
pp.49-52
PRMU, BioX 2018-03-18
15:20
Tokyo   Saliency Map Estimation for Omni-Directional Image Considering Prior Distribution
Tatsuya Suzuki, Takao Yamanaka (Sophia Univ.) BioX2017-50 PRMU2017-186
In recent years, the Deep Learning techniques have been applied to the estimation of saliency maps, which represent prob... [more] BioX2017-50 PRMU2017-186
pp.85-90
PRMU, MVE, IPSJ-CVIM [detail] 2018-01-18
11:50
Osaka   Comparison between saliency maps using top-down and bottom-up factors
Shoichi Adachi, Aya Shiraiwa (Tottori Univ.), Shigang Li (Hirosima City Univ.) PRMU2017-120 MVE2017-41
It is known that humans possess the ability to analyze complex scenes in real time. Based on this ability, saliency maps... [more] PRMU2017-120 MVE2017-41
pp.75-80
HIP 2017-10-24
10:00
Kyoto Kyoto Terrsa Scan path simulation in free-viewing condition based on a probabilistic saliency map model
Tomoya Okazaki, Takeshi Kohama (Kindai Univ.) HIP2017-69
Recently, saliency based mathematical models are frequently used to predict observers' gaze shifts. Although these model... [more] HIP2017-69
pp.57-60
MBE, NC
(Joint)
2017-05-26
09:55
Toyama Toyama Prefectural Univ. Characteristics of Gaze Estimation by Saliency Map Under Bottom-up Attention
Yuma Kobayashi, Hironobu Takano, Kiyomi Nakamura (Toyama Pref. Univ.) MBE2017-2
Saliency map is an estimation model of bottom-up attention which is derived with physical features.
However, the measur... [more]
MBE2017-2
pp.7-11
MBE, NC
(Joint)
2017-03-13
15:00
Tokyo Kikai-Shinko-Kaikan Bldg. Saliency-Based Analysis of Event-Related Potentials during Movie Viewing
Yasuyuki Hamada, Shin Ishii (Kyoto Univ.) NC2016-72
Human beings deal with much visual information in our daily life. Though natural movies can imitate such daily visual in... [more] NC2016-72
pp.49-53
ITS, IEE-ITS 2017-03-07
15:15
Kyoto Kyoto Univ. Estimating stress factors of an autonomous vehicle passenger using onboard videos labeled by several persons
Kohei Hagihara (NAIST), Norimichi Ukita (TTI), Masayuki Kanbara (NAIST), Hironori Hagita (ATR) ITS2016-88
Currently, various researches on autonomous driving are being conducted.
The purpose is to reduce traffic accidents du... [more]
ITS2016-88
pp.69-74
EID, ITE-IDY, ITE-HI, ITE-3DMT, IEE-OQD, SID-JC [detail] 2016-10-28
13:30
Tokyo Kikai-Shinko-Kaikan Bldg Comparison of Salient Feature for Material Appearance
Shoji Yamamoto (TMCIT), Yuto Hirasawa, Norimichi Tsumura (Chiba Univ.) EID2016-6
Material appearance, especially gloss, is very important visual cue of object recognition related to the surface smoothn... [more] EID2016-6
pp.5-8
HIP 2016-09-28
14:00
Nara   The Effect of Salience and Ensemble Information on Eye Movements in Visual Search
Shunsuke Kumakiri (Kyoto Univ.), Yoshiyuki Ueda (KokoronoMirai), Jun Saiki (Kyoto Univ.) HIP2016-56
The more salient point of the scene, the more it attracts visual attention (Itti & Koch, 2000). While saliency map is co... [more] HIP2016-56
pp.67-70
 Results 1 - 20 of 56  /  [Next]  
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