Faculty Profiles - YONEZAWA Takuro

Papers - YONEZAWA Takuro

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Time-Sensitive Cooperative Perception for Real-Time Data Sharing over Vehicular Communications: Overview, Challenges, and Future Directions Reviewed

Shunsuke Aoki, Takuro Yonezawa, Nobuo Kawaguchi, Peter Steenkiste, Ragunathan Raj Rajkumar

IEEE Internet of Things Magazine Vol. 5 ( 2 ) page： 108 - 113 2022.6

Deep Learning for Handwriting Recognition Using IMU-Equipped Pen Reviewed Open Access

NAGATA Yoshiteru, CHOYA Tomoki, SHIMOSATO Hironori, HIGASHIURA Keisuke, YAMAGUCHI Kohei, MURAI Daichi, SAKAKURA Namiki, FUKATANI Nobuya, URANO Kenta, TOIDE Yuta, KAWAGUCHI Nobuo, YONEZAWA Takuro

JSAI Technical Report, SIG-KBS Vol. 125 ( 0 ) page： 03 2022.3

<i>RobotNEST:</i> Toward a Viable Testbed for IoT-Enabled Environments and Connected and Autonomous Robots Reviewed

Shunsuke Aoki, Takuro Yonezawa, Nobuo Kawaguchi

IEEE Sensors Letters Vol. 6 ( 2 ) page： 1 - 4 2022.2

A Data-Driven Approach for Online Pre-impact Fall Detection with Wearable Devices Reviewed

Takuto Yoshida, Kazuma Kano, Keisuke Higashiura, Kohei Yamaguchi, Koki Takigami, Kenta Urano, Shunsuke Aoki, Takuro Yonezawa, Nobuo Kawaguchi

Sensor- and Video-Based Activity and Behavior Computing Vol. 291 page： 133 - 147 2022

MetaPo: A Robotic Meta Portal for Interspace Communication. Reviewed

Takuro Yonezawa, Nozomi Hayashida, Kenta Urano, Johannes Przybilla, Yutaro Kyono, Nobuo Kawaguchi

SIGGRAPH '22: Special Interest Group on Computer Graphics and Interactive Techniques Conference page： 28 - 2 2022

XR Communication System for Remote Control Wheelchairs. Reviewed

Hironori Shimosato, Nozomi Hayashida, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

Proceedings of the 12th International Conference on the Internet of Things(IOT) page： 219 - 223 2022

Synthetic People Flow: Privacy-Preserving Mobility Modeling from Large-Scale Location Data in Urban Areas. Reviewed

Naoki Tamura, Kenta Urano, Shunsuke Aoki 0001, Takuro Yonezawa, Nobuo Kawaguchi

MobiQuitous Vol. 419 page： 553 - 567 2022

Smartphone Localization with Solar-Powered BLE Beacons in Warehouse. Reviewed

Kazuma Kano, Takuto Yoshida, Nozomi Hayashida, Yusuke Asai, Hitoshi Matsuyama, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

Distributed, Ambient and Pervasive Interactions. Smart Environments, Ecosystems, and Cities - 10th International Conference Vol. 13325 page： 291 - 310 2022

大規模屋外施設におけるWi-Fiパケットセンサへの影響と利活用の検証 Reviewed Open Access

米澤拓郎

情報処理学会論文誌デジタルプラクティス Vol. 3 page： 12 - 21 2022

Deep Learning for Ballroom Dance Recognition: A Temporal and Trajectory-Aware Classification Model With Three-Dimensional Pose Estimation and Wearable Sensing Reviewed

Hitoshi Matsuyama, Shunsuke Aoki, Takuro Yonezawa, Kei Hiroi, Katsuhiko Kaji, Nobuo Kawaguchi

IEEE Sensors Journal Vol. 21 ( 22 ) page： 25437 - 25448 2021.11

An End-to-End BLE Indoor Localization Method Using LSTM Open Access

Urano Kenta, Hiroi Kei, Yonezawa Takuro, Kawaguchi Nobuo

Journal of Information Processing Vol. 29 ( 0 ) page： 58 - 69 2021

Language：English Publishing type：Research paper (scientific journal) Publisher：Information Processing Society of Japan

<p>This paper proposes an indoor localization method for Bluetooth Low Energy (BLE) devices using an end-to-end LSTM neural network. We focus on a large-scale indoor space where there is a tough environment for wireless indoor localization due to signal instability. Our proposed method adopts end-to-end localization, which means input is a time-series of signal strength and output is the estimated location at the latest time in the input. The neural network in our proposed method consists of fully-connected and LSTM layers. We use a custom-made loss function with 3 error components: MSE, the direction of travel, and the leap of the estimated location. Considering the difficulty of data collection in a short preparation term, the data generated by a simple signal simulation is used in the training phase, before training with a small amount of real data. As a result, the estimation accuracy achieves an average of 1.92m, using the data collected in GEXPO exhibition in Miraikan, Tokyo. This paper also evaluates the estimation accuracy assuming the troubles in a real operation.</p>

DOI： 10.2197/ipsjjip.29.58

Open Access

Scopus

CiNii Research

A Basic Study on Ballroom Dance Figure Classification with LSTM Using Multi-modal Sensor Reviewed

Hitoshi Matsuyama, Kei Hiroi, Katsuhiko Kaji, Takuro Yonezawa, Nobuo Kawaguchi

Smart Innovation, Systems and Technologies Vol. 204 page： 209 - 226 2021

A Gaze-Based Unobstructive Information Selection by Context-Aware Moving UI in Mixed Reality. Reviewed

Nozomi Hayashida, Hitoshi Matsuyama, Shunsuke Aoki, Takuro Yonezawa, Nobuo Kawaguchi

Distributed, Ambient and Pervasive Interactions - 9th International Conference Vol. 12782 page： 301 - 315 2021

Attention-Guidance Method Based on Conforming Behavior of Multiple Virtual Agents for Pedestrians Reviewed

Yoshida, N; Yonezawa, T

PROCEEDINGS OF THE 21ST ACM INTERNATIONAL CONFERENCE ON INTELLIGENT VIRTUAL AGENTS (IVA) page： 209 - 215 2021

Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents Iva 2021

Humans observe the behavior of others and exhibit conforming behavior according to the situation. In this study, we propose a method to change the user's walking behavior and attention by changing the ratio of multiple virtual agents in action. We verified whether the attention to a poster on the wall and the walking behavior of a pedestrian changed according to the type and proportion of actions exhibited by multiple agents presented to a particular pedestrian. The results showed that the participant's walking speed and attention to the wall advertisement changed according to the agents' walking behavior, such as deceleration and stopping.

DOI： 10.1145/3472306.3478346

Web of Science

Scopus

DigiMobot: Digital Twin for Human-Robot Collaboration in Indoor Environments. Reviewed

Yuto Fukushima, Yusuke Asai, Shunsuke Aoki, Takuro Yonezawa, Nobuo Kawaguchi

IEEE Intelligent Vehicles Symposium(IV) Vol. 2021-July page： 55 - 62 2021