KEIO RESEARCHERS INFORMATION SYSTEM

Career 【 Display / hide 】

Career 【 Display / hide 】

• 1992.04

  -

  1995.03

  慶應義塾大学（理工学部） ,助手

• 1994.04

  -

  1997.08

  日本体育大学 ,非常勤講師

• 1995.04

  -

  2001.03

  Assistant Professor, Keio University

• 1997.08

  -

  1999.08

  Visiting Scientist, Carnegie Mellon University

• 2001.04

  -

  2006.03

  Associate Professor, Keio University

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Academic Background 【 Display / hide 】

Academic Background 【 Display / hide 】

• 1987.03

  Keio University, Faculty of Science and Engineering, (電気工学科)

  University, Graduated

• 1989.03

  Keio University, Graduate School, Division of Science and Engineeri, 電気工学専攻

  Graduate School, Completed, Master's course

• 1992.03

  Keio University, Graduate School, Division of Science and Engineeri, 電気工学専攻

  Graduate School, Completed, Doctoral course

Academic Degrees 【 Display / hide 】

Academic Degrees 【 Display / hide 】

• 工学, Keio University, 1992.03

Research Areas 【 Display / hide 】

Research Areas 【 Display / hide 】

• Manufacturing Technology (Mechanical Engineering, Electrical and Electronic Engineering, Chemical Engineering) / Communication and network engineering (Information and Communication Engineering)

• Informatics / Theory of informatics (Computer Science)

Research Keywords 【 Display / hide 】

Research Keywords 【 Display / hide 】

• Computer Vision

• Pattern Recognition

• Human Interface

• Image Processing

Books 【 Display / hide 】

Books 【 Display / hide 】

• 人工生命「５．３　金融市場シミュレーションへの応用」分担

  尹　煕元，斎藤英雄，棚橋隆彦, 同文書院　編　井上春樹, 2002

  　View Summary

  金融市場の株価の変動をGAを用いて解析する手法を提案し，実際の価格変動データを利用して解析結果の妥当性を検討した．

• 'アドバンスド・センサ・ハンドブック, 「9-2-2 CT手法の産業応用」分担'

  '斎藤英雄, 中島真人', 培風館, 1994

  　View Summary

  CT手法の産業応用例について解説した。

Papers 【 Display / hide 】

Papers 【 Display / hide 】

• 3D Gaussian Reference Parts for Robust Free-Viewpoint Visual Inspection

  Ito K., Ueda S., Mori S., Sugano J., Adachi H., Saito H.

  IEEE Access 14   37885 - 37896 2026

  　View Summary

  Machine vision systems are crucial for quality control in manufacturing, ensuring that products meet standards through automatic in-line visual inspections. While reference images are typically used as benchmarks for comparison, a significant challenge arises when objects arrive at inspection points in misaligned orientations. This misalignment can lead to erroneous decisions by automated systems, resulting in false positives or negatives that increase waste and slow production. To address this issue, we propose a visual inspection pipeline that leverages recent machine-learning-based approaches. Our pipeline virtually reorients a 3D reference to the inspection target's orientation for comparison, effectively addressing the misalignment issue. Specifically, it integrates 3D Gaussian Splatting and MASt3R, enabling a robust 3D-based defect detection system that uses only a single camera sensor, thereby moving beyond traditional 2D image-based methods. We validated our approach in real-world scenarios by testing it on 20 synthetic objects and real industrial parts. The proposed pipeline maintains accuracy and processing speed comparable to those of existing methods.

  • Access to Document (DOI)

• 3D Gaussian Reference Parts for Robust Free-Viewpoint Visual Inspection

  Ito K., Ueda S., Mori S., Sugano J., Adachi H., Saito H.

  IEEE Access 14   37885 - 37896 2026

  　View Summary

  Machine vision systems are crucial for quality control in manufacturing, ensuring that products meet standards through automatic in-line visual inspections. While reference images are typically used as benchmarks for comparison, a significant challenge arises when objects arrive at inspection points in misaligned orientations. This misalignment can lead to erroneous decisions by automated systems, resulting in false positives or negatives that increase waste and slow production. To address this issue, we propose a visual inspection pipeline that leverages recent machine-learning-based approaches. Our pipeline virtually reorients a 3D reference to the inspection target's orientation for comparison, effectively addressing the misalignment issue. Specifically, it integrates 3D Gaussian Splatting and MASt3R, enabling a robust 3D-based defect detection system that uses only a single camera sensor, thereby moving beyond traditional 2D image-based methods. We validated our approach in real-world scenarios by testing it on 20 synthetic objects and real industrial parts. The proposed pipeline maintains accuracy and processing speed comparable to those of existing methods.

  • Access to Document (DOI)

• 3D Gaussian Reference Parts for Robust Free-Viewpoint Visual Inspection

  Ito K., Ueda S., Mori S., Sugano J., Adachi H., Saito H.

  IEEE Access 14   37885 - 37896 2026

  　View Summary

  Machine vision systems are crucial for quality control in manufacturing, ensuring that products meet standards through automatic in-line visual inspections. While reference images are typically used as benchmarks for comparison, a significant challenge arises when objects arrive at inspection points in misaligned orientations. This misalignment can lead to erroneous decisions by automated systems, resulting in false positives or negatives that increase waste and slow production. To address this issue, we propose a visual inspection pipeline that leverages recent machine-learning-based approaches. Our pipeline virtually reorients a 3D reference to the inspection target's orientation for comparison, effectively addressing the misalignment issue. Specifically, it integrates 3D Gaussian Splatting and MASt3R, enabling a robust 3D-based defect detection system that uses only a single camera sensor, thereby moving beyond traditional 2D image-based methods. We validated our approach in real-world scenarios by testing it on 20 synthetic objects and real industrial parts. The proposed pipeline maintains accuracy and processing speed comparable to those of existing methods.

  • Access to Document (DOI)

• 3D Gaussian Reference Parts for Robust Free-Viewpoint Visual Inspection

  Ito K., Ueda S., Mori S., Sugano J., Adachi H., Saito H.

  IEEE Access 14   37885 - 37896 2026

  　View Summary

  Machine vision systems are crucial for quality control in manufacturing, ensuring that products meet standards through automatic in-line visual inspections. While reference images are typically used as benchmarks for comparison, a significant challenge arises when objects arrive at inspection points in misaligned orientations. This misalignment can lead to erroneous decisions by automated systems, resulting in false positives or negatives that increase waste and slow production. To address this issue, we propose a visual inspection pipeline that leverages recent machine-learning-based approaches. Our pipeline virtually reorients a 3D reference to the inspection target's orientation for comparison, effectively addressing the misalignment issue. Specifically, it integrates 3D Gaussian Splatting and MASt3R, enabling a robust 3D-based defect detection system that uses only a single camera sensor, thereby moving beyond traditional 2D image-based methods. We validated our approach in real-world scenarios by testing it on 20 synthetic objects and real industrial parts. The proposed pipeline maintains accuracy and processing speed comparable to those of existing methods.

  • Access to Document (DOI)

• 8th ACM International Workshop on Multimedia Content Analysis in Sports (ACM MMSports'25)

  Lienhart R., Moeslund T.B., Saito H.

  Mm 2025 Proceedings of the 33rd ACM International Conference on Multimedia Co Located with mm 2025    14288 - 14290 2025.10

  　View Summary

  The 8th ACM International Workshop on Multimedia Content Analysis in Sports is held in Dublin, Ireland on October 28th, 2025. It is co-located with ACM Multimedia 2025. The goal of this workshop is to bring together researchers and practitioners from academia and industry to address challenges and report progress in mining, analyzing, understanding, and visualizing the multimodal data in sports. The combination of sports and modern technology offers a novel and intriguing field of research with promising approaches for visual broadcast augmentation as well as understanding, statistical analysis, and evaluation in amateur and professional sports. There is a lack of research communities focusing on the fusion of multiple modalities. Thus, this workshop series on multimedia content analysis in sports aims to contribute to the closure of this research gap by bringing together the breadth and depth of these diverse approaches to stimulate each other with new ideas and foster research progress.

  • Access to Document (DOI)

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Papers, etc., Registered in KOARA 【 Display / hide 】

Papers, etc., Registered in KOARA 【 Display / hide 】

• 編集後記

  Saito, Hideo

  DMC Review Keio University (慶應義塾大学デジタルメディア・コンテンツ統合研究センター)  2 ( 1 ) 62 - 62 2015.03

  ISSN  21883424

• 編集後記

  Saito, Hideo

  DMC Review Keio University (慶應義塾大学デジタルメディア・コンテンツ統合研究センター)  1 ( 1 ) 49 - 49 2014.03

  ISSN  21883424

• 3D visual media generation and mixed reality presentation by cooperative use of multiple handheld cameras

  Saito, Hideo

  科学研究費補助金研究成果報告書 2011

Reviews, Commentaries, etc. 【 Display / hide 】

Reviews, Commentaries, etc. 【 Display / hide 】

• Workshop chairs welcome

  Lienhart R., Moeslund T.B., Saito H.

  Mmsports 2023 Proceedings of the 6th International Workshop on Multimedia Content Analysis in Sports Co Located with mm 2023  2023.10

• Correction to: Semi-automation of gesture annotation by machine learning and human collaboration (Language Resources and Evaluation, (2022), 56, 3, (673-700), 10.1007/s10579-022-09586-4)

  Ienaga N., Cravotta A., Terayama K., Scotney B.W., Saito H., Busà M.G.

  Language Resources and Evaluation 56 ( 3 )  2022.09

  ISSN  1574020X

  　View Summary

  In the original publication of the article the section numbers were displayed incorrectly. This has been corrected now. The original article has been corrected.

  • Access to Document (DOI)

• Special issue on “drones as enablers of novel services: operational and technology challenges”

  Bernardos A.M., Besada J.A., Herrero J.G., Saito H., Marti P.

  Personal and Ubiquitous Computing 26 ( 4 ) 1083 - 1084 2022.08

  ISSN  16174909

  • Access to Document (DOI)

• MMSports'21 Workshop Chairs' Welcome

  Lienhart R., Moeslund T.B., Saito H.

  Mmsports 2021 Proceedings of the 4th International Workshop on Multimedia Content Analysis in Sports Co Located with ACM mm 2021  2021.10

• Workshop chairs’ welcome

  Lienhart R., Moeslund T.B., Saito H.

  MMSports 2019 - Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports, co-located with MM 2019 (MMSports 2019 - Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports, co-located with MM 2019)   2019.10

  ISSN  9781450369114

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Presentations 【 Display / hide 】

Presentations 【 Display / hide 】

• デジタルヒューマンモデルを用いた深層学習による物体組込型カメラ画像からの把持姿勢推 定

  稲生健太郎，家永直人，杉浦裕太，斎藤英雄，宮田なつき，多田充徳

  [Domestic presentation]  2018年電子情報通信学会総合大会, 

  2018.03

  , 

  Poster presentation, 電子情報通信学会

• 3D スキャン点群の建物のセグメンテーション

  王　麒雁，楊　亮，斎藤英雄，木下久史

  [Domestic presentation]  2018年電子情報通信学会総合大会, 

  2018.03

  , 

  Poster presentation, 電子情報通信学会

• 3次元点群を用いた単一視点画像による絶対スケール測定

  安藤隆平、斎藤英雄

  [Domestic presentation]  Dynamic Image processing for real Application workshop 2018 (中京大学 名古屋キャンパス) , 

  2018.03

  , 

  Oral presentation (general), 精密工学会 画像応用技術専門委員会

• 距離カメラ付きスマートフォンを用いた人体の足の3次元形状計測

  小林巧、家永直人、杉浦裕太、斎藤英雄、宮田なつき、多田充徳

  [Domestic presentation]  Dynamic Image processing for real Application workshop 2018 (中京大学 名古屋キャンパス) , 

  2018.03

  , 

  Oral presentation (general), 精密工学会 画像応用技術専門委員会

• 球面ドロネー三角形分割法を用いた3D-LiDAR点群の領域分割処理法

  田中季晃、大石圭、中島由勝、斎藤英雄

  [Domestic presentation]  Dynamic Image processing for real Application workshop 2018 (中京大学 名古屋キャンパス) , 

  2018.03

  , 

  Oral presentation (general), 精密工学会 画像応用技術専門委員会

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Research Projects of Competitive Funds, etc. 【 Display / hide 】

Research Projects of Competitive Funds, etc. 【 Display / hide 】

• Measurements and Visualization of Ultra High-Speed Phenomena Using Neuromorphic Vision

  2023.04

  -

  2027.03

  基盤研究(B), Principal investigator

Awards 【 Display / hide 】

Awards 【 Display / hide 】

• Fellow

  2017.03, the Institute of Electronics, Information and Communication Engineers

• Best Paper

  Yusuke Nakayama, Hideo Saito, Masayoshi Shimizu, and Nobuyasu Yamaguchi, 2016.02, IS & T, Marker-less AR framework using on-site 3D line segment based model generation

  Type of Award： International academic award (Japan or overseas),  Country： United States

• 査読功労賞

  2015.08, 映像情報メディが学会

  Type of Award： Award from Japanese society, conference, symposium, etc.

• Jon Campbell Best Paper Prize

  Y. Shinozuka, F. de Sorbier and H. Saito, 2014.08, Organising Committee of the Irish Machine Vision and Image Processing Conference 2014, Specular 3D Object Tracking by View Generative Learning

  Type of Award： International academic award (Japan or overseas),  Country： United Kingdom

• 活動功労賞

  斎藤英雄, 2014.06, 電子情報通信学会　情報・システムソサイエティ, パターン認識・メディア理解研究専門委員会活動への貢献

  Type of Award： Award from Japanese society, conference, symposium, etc.

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Courses Taught 【 Display / hide 】

Courses Taught 【 Display / hide 】

• COMPUTER VISION

  2026

• INTERNATIONAL INITIATIVE OVERSEAS 3

  2026

• VISUAL COMPUTING 1 B

  2026

• JINKAN-KOSAI PROJECT 3

  2026

• COMPREHENSIVE EXERCISE OF ELECTRONICS AND ELECTRICAL ENGINEERING

  2026

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Social Activities 【 Display / hide 】

Social Activities 【 Display / hide 】

• 「IAPR Workshop on Machine Vision Applications」

  1997.08

  -

  1998.11

• 「第3回画像センシングシンポジウム」 (1996年6月)

  1996.10

  -

  1997.06

• 「第2回画像センシングシンポジウム」 (1996年6月 13日、14日)

  1995.11

  -

  1996.06

• 「IAPR Workshop on Machine Vision Applications 」

  1995.09

  -

  1996.11

• 電子情報通信学会学生会連絡会

  1995.05

  -

  1997.05

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Memberships in Academic Societies 【 Display / hide 】

Memberships in Academic Societies 【 Display / hide 】

• 日本バーチャルリアリティ学会 複合現実感研究会, 

  2013.01

  -

  Present

• the 23rd International Conference on Artificial Reality and Telexistence (ICAT 2013), 

  2012.12

  -

  2013.12

• IPSJ Transactions on Computer Vision and Applications, MIRU Conference Editorial Board, 

  2012.10

  -

  Present

• 情報処理学会　コンピュータビジョンとイメージメディア研究会, 

  2012.04

  -

  Present

• 日本バーチャルリアリティ学会, 

  2012.04

  -

  Present

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Committee Experiences 【 Display / hide 】

Committee Experiences 【 Display / hide 】

• 2017.04

  -

  Present

  Editor in Chief, IPSJ Transactions on Computer Vision and Applications, Editorial Board

• 2016.06

  -

  2018.05

  副会長（技術会議担当）, 電子情報通信学会　情報システムソサイエティ

• 2016.04

  -

  2018.03

  評議員, 日本バーチャルリアリティ学会

• 2016.04

  -

  2018.03

  運営委員, 情報処理学会　コンピュータビジョンとイメージメディア研究会

• 2016.04

  -

  2017.03

  専門委員長, 電子情報通信学会　汎光線時空間映像学研究専門委員会

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