Interaction Group


Our group aims to realize "Human-Computer integration" which is easier to use and more cognizant by interaction design. In particular, we are researching how a computer system that is advanced and intelligent, such as automatic driving technology, sensing technology, machine learning etc., can be integrated with people.

This group considers how to contribute to the further evolution of humankind by integrating the technology evolved by humankind with humanity.

どんなに素晴らしい技術も人が使いやすくなくては意味がありません. 特に自動運転など,新しい技術,人の能力を超える技術をどのように人と結びつけるのか,様々な側面から研究を行っています.






Hiroki Saji(M2)

  • 佐治 拓樹,小林 和弘名大石黒 祥生名大,戸田 智基名大,大谷 健登名大,西野 隆典名城大,武田 一哉名大声質の可視化を用いた所望音声検索システムの提案第 133 回音楽情報科学研究会,2022年1月

Automatic Generation of Road Trip Summary Video for Reminiscence and Entertainment using Dashcam Video

Vehicle dashboard cameras are becoming an increasingly popular kind of automotive accessory. While it is easy to obtain the high-definition video data recorded by dashcams using Secure Digital memory cards, this data is rarely used except for safety purposes because it takes substantial time and effort to review or edit many hours of such recorded videos. In this paper, we propose a new usage for this data through the automatic video editing system we have developed that can create enjoyable video summaries of road trips utilizing video and other data from the vehicle. We also report the results of comparisons between automatically edited videos created by the proposed system and manually edited videos created by study participants. The prototype developed in this study and the findings from our experiments will contribute to improving the driving experience by providing entertainment for automobile users after road trips, and by memorializing their travels.

Kana Bito (M1)

  • Kana Bito, Itiro Siio, Yoshio Ishiguro, and Kazuya Takeda. 2021. Automatic Generation of Road Trip Summary Video for Reminiscence and Entertainment using Dashcam Video. In 13th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '21), September 9–14, 2021, Leeds, United Kingdom. ACM, New York, NY, USA, 10 Pages.

  • 尾頭花奈, 石黒祥生, 椎尾一郎, 武田一哉, ドライブレコーダのデータから旅行の思い出動画を自動生成するwebサービスの実装, ソフトウェア科学会WISS2021論文集, No. 94, pp. 71-77, 静岡県浜松市, 2021.12.8-10. (査読あり,ショートペーパー採択)

  • 公開したwebシステム:



Yusuke Sakai (D3)

  • 榮井 優介,石黒 祥生,大谷 健登,西野 隆典,武田 一哉,FollowSelect: 直観的なナビゲーションが可能な経路追従型のメニュー選択手法,情報処理学会論文誌 ユビキタスコンピューティングシステム(X)特集,62巻10号,2021年10月.

  • 榮井 優介,石黒 祥生,西野 隆典,武田 一哉, FollowSelect: 準備動作が必要な機器の利用に適した経路追従型メニュー選択手法, 情報処理学会 インタラクション2020 インタラクティブ発表, 2A-02, pp. 512-516, 2020年3月(インタラクティブ発表).

Manipulation of Speed Perception while in Motion using Auditory Stimuli

Due to the rapid development of automated driving technology, the issue of how people will spend their time when traveling in fully automated vehicles is attracting much attention. Infotainment systems that use virtual reality (VR) environments have been proposed as a way to occupy the passengers of automated vehicles when human intervention in the driving process is no longer necessary. In the present study, we investigate whether a passenger’s speed perception can be manipulated using only auditory stimuli, by having them listen to the sound of an engine accelerating, moving at a constant speed, or decelerating without any visual stimuli. We experimentally verify that it is possible to manipulate a passenger’s subjective perception of speed, based on participant feedback, although no significant difference in their perception of speed was observed in our objective evaluation.

Yuta Kanayama(M1)

  • Yuta Kanayama, Yoshio Ishiguro, Takanori Nishino, Kento Ohtani, and Kazuya Takeda. 2021. Ubiquitous Robots2021, pp.332-335



Shumpei Okawa(M1)


In this paper we propose an interactive system that allows only the owner of a target object to secretly find it among other similar or identical objects, which we call SecretSign. Finding a personal object, e.g. an assigned vehicle in a car-sharing parking lot, where there are many cars that look the same or are similar, can be difficult. In addition, we may not want to notify other people which object we are looking for, e.g. a car thief waiting to steal a car when the driver opens the door. Our proposed system allows a user to find an object without notifying others of the target, using a light attached to the target object which turns on and off in conjunction with user's operation of a remote control device, while lights on the other objects turn on and off randomly.

Hiromi Morita (B4, Alumni) , Yusuke Sakai (D1)

Improving target selection accuracy for vehicle touch screens

When operating the touch screen in a car, the touch point can shift due to the vibration, resulting in selection errors. Using larger target is a possible solution, but this significantly limits the amount of content that can be displayed on the touch screen. Therefore, we propose a method for in-vehicle touch screen target selection that can be used with a variety of sensors to increase selection accuracy.

Kosuke Ito (M2)

Effects on User Perception of a 'Modified' Speed Experience Through In-Vehicle Virtual Reality

In order to make the experience of traveling in automated vehicles more enjoyable, Virtual Reality (VR) experiences based on the real-world journey have been proposed. Presenting users with VR content synched to the car's actual movement decreases the motion sickness, but it also sharply limits the possible range of VR content. In this paper, we investigate whether the user's subjective perception of speed can be 'modified' by presenting VR content at a different speed than the actual speed of the vehicle, and whether users feel this experience is strange. Study participants viewed VR content occurring at a faster or slower speed than their actual travel speed in an electric wheelchair. Our results show that the participants were able to do this without experiencing a feeling of "strangeness". However, the participants did report higher "strangeness" scores when the speed in the VR content was slower than their actual speed.

Toshimitsu Watababe(B4, Alumni), Yusuke Sakai(D1)



Yusuke Sakai (D1)