Faculty Profiles - Nakazawa Atsushi

MISC - Nakazawa Atsushi

Division display 21 - 40 of about 169 ／ All the affair displays >>

ソーシャルロボットによる眠気抑制効果

原航基, 中澤篤志, 竹本あゆみ

電子情報通信学会HCGシンポジウム 2021.5

角膜表面反射画像からのシーン識別

大嶋佑紀, 前田響介, 枝本祐典, 中澤篤志

電子情報通信学会技術研究報告(Web) 120 ( 393(BioX2020 40-48) ) 2021

Deep Facial Expression Transfer: StyleGAN-based Facial Motion Transfer

竹内至生, 中澤篤志

電子情報通信学会技術研究報告(Web) 120 ( 389(IMQ2020 10-35) ) 2021

自閉スペクトラム症児の母子相互作用のマルチモーダル分析快情動の表出と顔向けの共起関係

長岡千賀, 松島佳苗, アンミー, 伊藤凌太朗, 加藤寿宏, 吉川左紀子, 中澤篤志, 本田美和子, ジネストイヴ, 安藤夏子, 岩元美由紀

日本心理学会大会発表抄録集 85th 2021

自閉スペクトラム症児の母子相互作用のマルチモーダル分析 : 言語発達の水準が異なる2事例の比較—A multimodal analysis of mother-child interaction in children with ASD : Comparison between two children with different level of language development—第182回ヒューマンインタフェース学会研究会コミュニケーション支援および一般

松島佳苗, 長岡千賀, アンミー, 伊藤凌太朗, 加藤寿宏, 吉川左紀子, 中澤篤志, 本田美和子, イヴジネスト, 安藤夏子, 岩元美由紀

ヒューマンインタフェース学会研究報告集 23 11 - 16 2021

Analysis of Hand Contact Surface for Touching Motion Toward End-effector to Reproduce Humanitude’s Touching

豊田真行, 湯口彰重, CHO Sung-Gwi, 佐藤勇起, 高松淳, 中澤篤志, 和田隆広, 小笠原司

計測自動制御学会システムインテグレーション部門講演会(CD-ROM) 22nd 2021

より良い聞き手のためのアンドロイドによる瞬目と頷きの模倣効果の検討

湯口彰重, GARCIA RICARDEZ Gustavo Alfonso, 高松淳, 中澤篤志, 小笠原司

日本ロボット学会学術講演会予稿集(CD-ROM) 38th 2020

Imitation of Human Eyeblinks and Nodding Using an Android Toward Attentive Listening

湯口彰重, 高松淳, 中澤篤志, 小笠原司

日本機械学会ロボティクス・メカトロニクス講演会講演論文集(CD-ROM) 2020 2020

Correlation analysis of personality by using home life behavior measurements

沼田崇志, 工藤泰幸, 加藤猛, 金子迪大, 野村理朗, 森口佑介, 中澤篤志, 嶺竜治

情報処理学会研究報告(Web) 2020 ( HCI-190 ) 2020

人工知能によって「人を見る」~人の目を測る・人の行動を測る・介護の上手さを測る~

中澤篤志

学習院大学計算機センター年報 40 120 - 129 2020

ロボットによる見る・触れる動作の模倣とそれを通じた評価

高松淳, 豊島健太, 佐野哲也, 湯口彰重, 中澤篤志, ALFONSO Garcia Ricardez Gustavo, 丁明, 小笠原司

日本ロボット学会学術講演会予稿集(CD-ROM) 37th 2019

ユマニチュードを行動から，脳から知りたい，

中澤篤志

医学界新聞 3154号 13 2018

人の視線計測に基づく会話時の視線提示が可能なアンドロイドシステム

佐野哲也, 湯口彰重, 中澤篤志, GARCIA Gustavo, 高松淳, 小笠原司

計測自動制御学会システムインテグレーション部門講演会(CD-ROM) 19th 2018

PRMU基礎研究におけるオープンアイデア~PRMU第二期グランドチャレンジ~

安倍満, 舩冨卓哉, 木村昭悟, 中澤篤志, 山崎俊彦, 松下康之, 内田誠一, 前田英作

電子情報通信学会技術研究報告 117 ( 362(PRMU2017 101-111) ) 39 2017.12

Estimation of task difficulty and habituation effect while visual manipulation using pupillary response Reviewed

Asami Matsumoto, Yuta Tange, Atsushi Nakazawa, Toyoaki Nishida

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10165 24 - 35 2017

Language：English Publishing type：Article, review, commentary, editorial, etc. (international conference proceedings) Publisher：Springer Verlag

In this paper, we show the relationship between pupil dilation and visualmanipulation tasks to measure the magnitude of individual habituation effect and task difficulty. Our findings show that pupil dilation can be used as a new physiological signal in the application of audience measurement, affective computing, affective communications, and user interface design. We built a pointer maze game where a subject moves a pointer from start to end positions on a straight pathway, and we observe the subject’s pupil size while changing the pathway width and performing the game repeatedly. Through the two experiments, we found the maximum pupil size increases during the game when the pathway narrows. The first experiment indicates the difficulty of the task (narrower pathway) is related to the larger pupil diameter. On the basis of these results, we built models relating to (1) pupil size and pathway width, (2) pupil size and duration, and (3) pathway width and duration. The second experiment indicates the pupil constriction is related to the habituation effect of the users. While a similar effect has already been reported, the magnitude of pupil dilation during our task was about ten times as high as that in other tasks, so our confidence in the model is high.

DOI： 10.1007/978-3-319-56687-0_3

Scopus

researchmap

Evaluation of face-to-face communication skills for people with dementia using a head-mounted system Reviewed

Nakazawa, A, Okino Y, Honda M

3rd International Workshop on Pattern Recognition for Healthcare Analytics 2016.12

Point of Gaze Estimation Using Corneal Surface Reflection and 360° Spherical Image

116 ( 208 ) 75 - 81 2016.9

Evaluation of Care Skills using a Head-mounted Camera

116 ( 39 ) 95 - 100 2016.5

Heat map visualization of multi-slice medical images through correspondence matching of video frames Reviewed

Divesh Lala, Atsushi Nakazawa

2016 ACM SYMPOSIUM ON EYE TRACKING RESEARCH & APPLICATIONS (ETRA 2016) 119 - 122 2016

Language：English Publishing type：Research paper, summary (international conference) Publisher：ASSOC COMPUTING MACHINERY

Visual inspection of medical imagery such as MRI and CT scans is a major task for medical professionals who must diagnose and treat patients without error. Given this goal, visualizing search behavior patterns used to recognize abnormalities in these images is of interest. In this paper we describe the development of a system which automatically generates multiple image-dependent heat maps from eye gaze data of users viewing medical image slices. This system only requires the use of a non-wearable eye gaze tracker and video capturing system. The main automated features are the identification of a medical image slice located inside a video frame and calculation of the correspondence between display screen and raw image eye gaze locations. We propose that the system can be used for eye gaze analysis and diagnostic training in the medical field.

DOI： 10.1145/2857491.2857504

Web of Science

researchmap

Noise stable image registration using Random Resample Consensus Reviewed

Atsushi Nakazawa

2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR) 853 - 858 2016

Language：English Publishing type：Article, review, commentary, editorial, etc. (international conference proceedings) Publisher：IEEE COMPUTER SOC

Image registration is an important and fundamental problem in computer vision and image processing. Although there are currently a large number of image registration algorithms such as RANSAC and its extensions, image registration under very noisy conditions remains difficult when it cannot obtain enough number of correct corresponding points. This paper solves this issue by introducing a random resample consensus (RANRESAC) strategy, which achieves robust registration where it is difficult to obtain enough numbers of correct correspondence pairs. In contrast to RANSAC, proposed RANRESAC newly generate corresponding points for the images using the hypothesis transformation function, and verifies the correctness by evaluating the similarity of the local features at the newly sampled points. To confirm the effectiveness for the proposed method, we first conducted an preliminary experiment that evaluates the similarity of texture and orientation components of SURF local descriptor in the images adding several levels of noise. As the result, we observed the texture component is more stable than the orientation component. Based on this finding, we design the RANRESAC algorithm and performed experiments using a open image registration dataset. As the result, proposed method outperforms to the RANSAC, MSAC and Optimal RANSAC algorithms in large noise conditions.

DOI： 10.1109/ICPR.2016.7899742

Web of Science

researchmap

　 PREV - NEXT 　

< Nakazawa Atsushi >

MISC - Nakazawa Atsushi