Updated on 2025/06/09

写真a

 
MASAI KATSUTOSHI
 
Organization
Faculty of Information Science and Electrical Engineering Department of Advanced Information Technology Assistant Professor
School of Engineering Department of Electrical Engineering and Computer Science(Concurrent)
Graduate School of Information Science and Electrical Engineering Department of Information Science and Technology(Concurrent)
Title
Assistant Professor
Contact information
メールアドレス
Tel
09063705657
Profile
"Wearable facial expression recognition using light sensors" "Exploring methods for facilitating communication in VR" "HCI/VR technologies for supporting the acquisition of sports skills"
External link

Degree

  • Ph.D in Engineering

Research Interests・Research Keywords

  • Research theme: - Wearable facial expression recognition system using optical sensor array - VR/IoT sports support system

    Keyword: Human Computer Interaction, Affective Computing, Wearable Computing

    Research period: 2023.6 - 2025.12

Awards

  • 第19回日本バーチャルリアリティ学会論文賞

    2017.9   バーチャルリアリティ学会   正井克俊,杉浦裕太,尾形正泰,クンツェ カイ,稲見昌彦,杉本麻樹「AffectiveWear: 装着者の日常的な表情を認識する眼鏡型装置」(論文誌,Vol.21, No.2 pp.-385-394,2016)

Papers

  • Seamless Avatar Expression Transfer: Merging Camera and Smart Eyewear Embedded with Photo-Reflective Sensor Technologies

    Masai Katsutoshi

    2024.3

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    Language:English   Publisher:IEEE  

    Virtual Reality (VR) offers new ways to interact that are different from usual communication in the real world. In VR, avatars are key displays for showing users’ feelings and personalities non-verbally. Addressing the need for more convenient and continuous expression representation, we introduce a novel method for facial expression transfer in VR. This method integrates camera systems with photoreflective sensors embedded in eyewear, overcoming the limitations of traditional camera-based tracking. By offering smoother tracking and reducing manual calibration needs, this approach highlights the potential of multimodal technology to enhance non-verbal communication in virtual environments. Building on this, we demonstrated the example implementation of smile transfer and discussed future direction.

    CiNii Research

  • 顔の自己類似度が AI エージェントの印象に与える影響の解析 Reviewed

    @丹羽将康, 正井克俊, @吉田成朗, @杉本麻樹

    情報処理学会論文誌   2024.1

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

  • Seamless Avatar Expression Transfer: Merging Camera and Smart Eyewear Embedded with Photo-Reflective Sensor Technologies

    Masai, K

    2024 IEEE CONFERENCE ON VIRTUAL REALITY AND 3D USER INTERFACES ABSTRACTS AND WORKSHOPS, VRW 2024   591 - 593   2024   ISBN:979-8-3503-7450-6

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    Publisher:Proceedings - 2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2024  

    Virtual Reality (VR) offers new ways to interact that are different from usual communication in the real world. In VR, avatars are key displays for showing users' feelings and personalities non-verbally. Addressing the need for more convenient and continuous expression representation, we introduce a novel method for facial expression transfer in VR. This method integrates camera systems with photo-reflective sensors embedded in eyewear, overcoming the limitations of traditional camera-based tracking. By offering smoother tracking and reducing manual calibration needs, this approach highlights the potential of multimodal technology to enhance non-verbal commu-nication in virtual environments. Building on this, we demonstrated the example implementation of smile transfer and discussed future direction.

    DOI: 10.1109/VRW62533.2024.00114

    Web of Science

    Scopus

  • Analyzing the Effect of Diverse Gaze and Head Direction on Facial Expression Recognition With Photo-Reflective Sensors Embedded in a Head-Mounted Display.

    Fumihiko Nakamura, Masaaki Murakami, Katsuhiro Suzuki, Masaaki Fukuoka, Katsutoshi Masai, Maki Sugimoto

    IEEE Transactions on Visualization and Computer Graphics   29 ( 10 )   4124 - 4139   2023.10   ISSN:1941-0506

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    Language:Others   Publishing type:Research paper (scientific journal)   Publisher:IEEE Transactions on Visualization and Computer Graphics  

    As one of the facial expression recognition techniques for Head-Mounted Display (HMD) users, embedded photo-reflective sensors have been used. In this paper, we investigate how gaze and face directions affect facial expression recognition using the embedded photo-reflective sensors. First, we collected a dataset of five facial expressions (Neutral, Happy, Angry, Sad, Surprised) while looking in diverse directions by moving 1) the eyes and 2) the head. Using the dataset, we analyzed the effect of gaze and face directions by constructing facial expression classifiers in five ways and evaluating the classification accuracy of each classifier. The results revealed that the single classifier that learned the data for all gaze points achieved the highest classification performance. Then, we investigated which facial part was affected by the gaze and face direction. The results showed that the gaze directions affected the upper facial parts, while the face directions affected the lower facial parts. In addition, by removing the bias of facial expression reproducibility, we investigated the pure effect of gaze and face directions in three conditions. The results showed that, in terms of gaze direction, building classifiers for each direction significantly improved the classification accuracy. However, in terms of face directions, there were slight differences between the classifier conditions. Our experimental results implied that multiple classifiers corresponding to multiple gaze and face directions improved facial expression recognition accuracy, but collecting the data of the vertical movement of gaze and face is a practical solution to improving facial expression recognition accuracy.

    DOI: 10.1109/TVCG.2022.3179766

    Scopus

    researchmap

  • Investigating Effects of Facial Self-Similarity Levels on the Impression of Virtual Agents in Serious/Non-Serious Contexts.

    Masayasu Niwa, Katsutoshi Masai, Shigeo Yoshida, Maki Sugimoto

    Proceedings of the Augmented Humans International Conference 2023(AHs)   221 - 230   2023.3   ISBN:9781450399845

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    Language:Others   Publishing type:Research paper (other academic)   Publisher:ACM  

    Recent technological advances have enabled the use of AI agents to assist with human tasks and augment human cognitive abilities in a variety of contexts, including decision making. It is critical that users trust these AI agents in order to use them effectively. Given that people tend to trust other people who are similar to themselves, incorporating features of one's own face into the AI agent's face may improve one's trust in the AI agent. However, it is still unclear how impressions differ when comparing agents with the same appearance as one's own and some similarities under the same conditions. Recognizing the appropriate level of similarity when using a self-similar agent is important for establishing a trustworthy agent relationship between people and the AI agent. Therefore, we investigated the effect of the degree of self-similarity of the face of the AI agent on the user's trust in the agent. We examined users' impressions of four AI agents with different degrees of face self-similarity in different scenarios. The results showed that the AI agent, whose similarity to the user's facial feature was slightly recognizable but not obvious, received higher ratings on the feeling of closeness, attractiveness, and facial preferences. These self-similar AI agents were also more trustworthy in everyday non-serious decisions and were more likely to improve people's trustworthiness in such situations. Finally, we discuss the potential applications of our findings to design real-world AI agents.

    DOI: 10.1145/3582700.3582721

    Scopus

    researchmap

    Other Link: https://dblp.uni-trier.de/db/conf/aughuman2/ahs2023.html#NiwaMYS23

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Presentations

  • Koki Kawamura, Shunichi Kasahara, Masaaki Fukuoka, Katsutoshi Masai, Ryota Kondo, Maki Sugimoto International conference

    @Koki Kawamura, @Shunichi Kasahara, @Masaaki Fukuoka, Katsutoshi Masai, @Ryota Kondo, @Maki Sugimoto

    ACM SIGGRAPH 2023 Emerging Technologies  2023.7 

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    Event date: 2024.4

    Language:English  

    Venue:Los Angeles   Country:United States  

    Other Link: https://dl.acm.org/doi/abs/10.1145/3588037.3595401

  • Seamless Avatar Expression Transfer: Merging Camera and Smart Eyewear Embedded with Photo-Reflective Sensor Technologies International conference

    Katsutoshi Masai

    IEEE VR  2024.3 

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    Event date: 2024.3

    Language:English   Presentation type:Symposium, workshop panel (public)  

    Venue:Orland, Florida   Country:United States  

    Repository Public URL: https://hdl.handle.net/2324/7173605

  • Unobtrusive Refractive Power Monitoring: Using EOG to Detect Blurred Visio International conference

    @Xin Wei, @Huakun Liu,@Monica Perusquía-Hernández,Katsutoshi Masai,@Naoya Isoyama,@Hideaki Uchiyama,@Kiyoshi Kiyokawa

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Copy Persistent Link Browse Title List Sign up for Conference Alerts  2023.7 

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    Event date: 2023.7

    Language:English   Presentation type:Oral presentation (general)  

    Venue:シドニー   Country:Australia  

    The rise in population and aging has led to a significant increase in the number of individuals affected by common causes of vision loss. Early diagnosis and treatment are crucial to avoid the consequences of visual impairment. However, in early stages, many visual problems are making it difficult to detect. Visual adaptation can compensate for several visual deficits with adaptive eye movements. These adaptive eye movements may serve as indicators of vision loss. In this work, we investigate the association between eye movement and blurred vision. By using Electrooculography (EOG) to record eye movements, we propose a new tracking model to identify the deterioration of refractive power. We verify the technical feasibility of this method by designing a blurred vision simulation experiment. Six sets of prescription lenses and a pair of flat lenses were used to create different levels of blurring effects. We analyzed binocular movements through EOG signals and performed a seven-class classification using the ResNet18 architecture. The results revealed an average classification accuracy of 94.7% in the subject-dependent model. However, the subject-independent model presented poor performance, with the highest accuracy reaching only 34.5%. Therefore, the potential of an EOG-based visual quality monitoring system is proven. Furthermore, our experimental design provides a novel approach to assessing blurred vision.

    Other Link: https://ieeexplore.ieee.org/abstract/document/10341004

MISC

  • 光学透過型HMDを用いたAR-SSVEPにおける背景と奥行きの影響の検討

    坪地航己, 小林明美, 小林明美, 正井克俊, 正井克俊, 杉本麻樹, 木村聡貴, 木村聡貴

    日本バーチャルリアリティ学会大会論文集(CD-ROM)   27th   2022   ISSN:1349-5062

  • Gesture Definition for Turning Mask Strings into Input Interface and Prototyping

    山本匠, 正井克俊, WITHANA Anusha, 杉浦裕太

    情報処理学会研究報告(Web)   2022 ( EC-65 )   2022

  • バーチャル環境を用いた野球打撃の認知運動スキルの評価

    谷湧日, 小林明美, 小林明美, 福田岳洋, 正井克俊, 正井克俊, 杉本麻樹, 木村聡貴, 木村聡貴

    日本バーチャルリアリティ学会大会論文集(CD-ROM)   27th   2022   ISSN:1349-5062

Industrial property rights

Patent   Number of applications: 1   Number of registrations: 0
Utility model   Number of applications: 0   Number of registrations: 0
Design   Number of applications: 0   Number of registrations: 0
Trademark   Number of applications: 0   Number of registrations: 0

Professional Memberships

  • IEEE

Academic Activities

  • program committee member International contribution

    the 25th ACM International Conference on Multimodal Interaction (ICMI 2023)  ( Paris, France on October 9-13, 2023. France ) 2024.10

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    Type:Competition, symposium, etc. 

  • program committee member International contribution

    ACM TEI 2024  ( Cork, Ireland Ireland ) 2024.2

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    Type:Competition, symposium, etc. 

Research Projects

  • 装着型装置を用いた日常における自然な表情計測技術の構築

    Grant number:18J12580  2018 - 2019

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)

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    Grant type:Scientific research funding

Educational Activities

  • データサイエンス実践I~Ⅳ
    データサイエンス発展I,Ⅱ

Class subject

  • データサイエンス発展Ⅰ~Ⅱ

    2024.10 - 2025.3   Second semester

  • プログラミング演習(P)

    2024.6 - 2024.8   Summer quarter

  • データサイエンス実践Ⅰ~Ⅳ

    2024.4 - 2024.9   First semester

  • プログラミング演習(P)

    2024.6 - 2024.8   Summer quarter

FD Participation

  • 2023.11   Role:Participation   Title:【シス情FD】企業等との共同研究の実施増加に向けて

    Organizer:[Undergraduate school/graduate school/graduate faculty]

  • 2023.10   Role:Participation   Title:【シス情FD】価値創造型半導体人材育成センターについて

    Organizer:[Undergraduate school/graduate school/graduate faculty]

  • 2023.7   Role:Participation   Title:【シス情FD】若手教員の研究紹介⑨

    Organizer:[Undergraduate school/graduate school/graduate faculty]

  • 2023.6   Role:Participation   Title:【シス情FD】SBRC、QRECの活動ご紹介

    Organizer:[Undergraduate school/graduate school/graduate faculty]

  • 2023.5   Role:Participation   Title:【シス情FD】農学研究院で進めているDX教育について

    Organizer:[Undergraduate school/graduate school/graduate faculty]

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Visiting, concurrent, or part-time lecturers at other universities, institutions, etc.

  • 2024  慶應義塾大学情報理工学科  Classification:Affiliate faculty  Domestic/International Classification:Japan 

    Semester, Day Time or Duration:通年

  • 2023  慶應義塾大学情報理工学科  Classification:Affiliate faculty  Domestic/International Classification:Japan 

    Semester, Day Time or Duration:通年

Travel Abroad

  • 2015.12 - 2016.2

    Staying countory name 1:Australia   Staying institution name 1:University of South Australia