論文 - 河口　信夫

360 Robot Hand Interaction for Group Telepresence with MetaPo

Watanabe Y., Hayashida N., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

ACM International Conference Proceeding Series     頁： 183 - 185   2023年11月

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：ACM International Conference Proceeding Series  

In this demonstration paper, we present the RHS360, a 360-degree robotic hand system designed to facilitate communication across spatial domains. The RHS360 is capable of providing continuous alignment between the user's position in the cyber space and the robotic hand's position. Furthermore, it allows users in the cyber space to reposition the robotic hand to accommodate their movements within the space. Our system not only enables communication, including gestures, through the use of the robotic hand but also provides essential social cues that are crucial in effective communication.

DOI： 10.1145/3627050.3630730

Scopus

Wildlife Spotting and Sharing System for Kenyan Safari Game Drives

Shimura K., Katayama S., Urano K., Leleito E., Yonezawa T., Kawaguchi N.

ACM International Conference Proceeding Series     頁： 150 - 153   2023年11月

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：ACM International Conference Proceeding Series  

Traditional wildlife spotting on Kenyan Safari Game Drives, rooted in visual scouting and sporadic communication, encounters challenges in animal detection efficiency and environmental preservation. In light of rejuvenating post-pandemic tourism and enhancing safari experiences, this study proposes a wildlife spotting and sharing system. The methodology melds wildlife detection and sharing technologies, anchored by three core principles: preserving chance of encounters, regulating information accessibility, and endorsing environmental conservation. The system architecture employs sensors, GPS, and tablet terminals for real-Time data acquisition, animal identification, and information propagation. This approach aims to nurture an engaging, efficient, and eco-conscious wildlife spotting and sharing experience, potentially setting a benchmark for sustainable wildlife tourism in similar wildlife-rich regions.

DOI： 10.1145/3627050.3630727

Scopus

360 Robot Hand System for Omni-directional Interaction by Multiple Users

Watanabe Y., Hayashida N., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

ACM International Conference Proceeding Series     頁： 295 - 299   2023年11月

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：ACM International Conference Proceeding Series  

The rise of diverse digital environments like digital twins and the metaverse emphasizes the importance of telepresence methods for linking users across different spaces. These methods aim to boost communication and services between these spaces. This paper introduces RHS360, a 360-degree robot hand system designed for inter-spatial communication. RHS360 ensures the robot hand aligns precisely with the user in cyberspace, adjusting based on the user's movements in the virtual realm. This enables the robot hand not only to aid communication and gestures but also to convey crucial social cues, enhancing the overall communication experience. Additionally, a user survey was conducted, revealing that observing the robot hand's movements significantly improved understanding their partner's thoughts and fostered a greater sense of intimacy. These findings suggest that the proposed method enhances communication between different spaces.

DOI： 10.1145/3627050.3631573

Scopus

Gait-Robust Heading Estimation Using Horizontal Acceleration for Smartphone-based PDR 査読有り

Kazuma Kano, Takuto Yoshida, Shin Katayama, Kenta Urano, Takuro Yonezawa, and Nobuo Kawaguchi

Proceedings of the Work-in-Progress Papers at the 13th International Conference on Indoor Positioning and Indoor Navigation (IPIN-WiP 2023)     2023年9月

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）  

Scopus

天伏図作成補助システムにおける 全方位カメラを用いた天井設備の多視点画像抽出手法

小濱 大輝, 永田 吉輝, 安武 和成, 浦野 健太, 片山 晋, 米澤 拓郎, 河口 信夫

2023年(第41回)電気設備学会全国大会     2023年8月

駅ホームの人流センサおよび改札通過情報による電車乗降情報の分析

浦野 健太，米澤 拓郎，河口 信夫

第51回可視化情報シンポジウム     2023年8月

LiDARの視野を考慮した能動的な人流計測手法の検討

下里 浩昇，片山 晋，浦野 健太，米澤 拓郎，河口 信夫

第51回可視化情報シンポジウム     2023年8月

Mobility Link XR: Interspace Interaction System in Electric Wheelchair

Hayashida N., Shimosato H., Urano K., Yonezawa T., Kawaguchi N.

Communications in Computer and Information Science   1833 CCIS 巻   頁： 314 - 320   2023年7月

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：Communications in Computer and Information Science  

This research proposes a communication system called Mobility Link XR that connects physical space and cyberspace with mobility. Mobility Link XR is a system that enables remote users to view panoramic video from a 360-degree camera attached to a mobility vehicle in different space by wearing a VR device, and mobility users to view the remote user as an avatar by wearing an MR device. In this way, sharing space in three dimensions using XR enables a higher level of human communication. In this paper, we apply Mobility Link XR to an electric wheelchair and design two types of scenarios: an assistance mode that reproduces the positional relationship of communication in a conventional wheelchair, and a passenger mode that reproduces the positional relationship inside a vehicle, which is said to be a suitable distance for conversation. We also evaluated the reproducibility of communication in the wheelchair and the effectiveness of communication using the avatar. The results showed that the reproducibility of voice and emotion was highly evaluated and that the side-by-side positional relationship enabled higher quality communication as the avatar was more easily seen and felt present.

DOI： 10.1007/978-3-031-35992-7_43

Scopus

Understanding Regional Characteristics Through EC Data Analysis 査読有り

Yamaguchi K., Shoji K., Tamura N., Sakakura N., Matsukura Y., Hiranaga Y., Shimomura K., Urano K., Yonezawa T., Kawaguchi N.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   14036 LNCS 巻   頁： 390 - 404   2023年7月

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）  

DOI： 10.1007/978-3-031-34668-2_26

Scopus

Open-Domain Dialogue Management Framework Across Multiple Device for Long-Term Interaction 査読有り

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   14013 LNCS 巻   頁： 354 - 365   2023年7月

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（学術雑誌）  

DOI： 10.1007/978-3-031-35602-5_25

Scopus

点群データと基盤地図情報を用いた屋外自律移動ロボット向け地図の生成手法 査読有り Open Access

相川雄也, 浦野 健太, 片山 晋, 米澤 拓郎, 河口 信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム     2023年7月

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Open Access

インスタンスセグメンテーションを用いたトラックバース状況の分析 査読有り Open Access

横山皓大, 片山 晋, 浦野 健太, 米澤 拓郎, 河口 信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム     2023年7月

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Open Access

全方位カメラによる設備外形を考慮した天井パノラマ画像合成手法 査読有り Open Access

小濱 大輝, 永田 吉輝, 安武 和成, 浦野 健太, 片山 晋, 米澤 拓郎, 河口 信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム     2023年7月

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Open Access

天井設置型の複数マイクと話者の位置情報を用いた発話方向推定手法 査読有り Open Access

市川 直人, 戸出 悠太 , 片山 晋, 浦野 健太, 米澤 拓郎, 河口 信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム     2023年7月

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Open Access

複数ユーザによる全方位インタラクションを可能にする360ロボットハンドシステム 査読有り Open Access

渡辺 圭貴，林田 望海，片山 晋，浦野 健太，米澤 拓郎，河口 信夫

マルチメディア，分散，協調とモバイル(DICOMO2023)シンポジウム     2023年7月

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Open Access

通過情報を活用した移動経路分析・応用手法の評価と応用

永田 吉輝, 浦野 健太, 米澤 拓郎, 河口 信夫

第78回UBI研究会     2023年5月

滞在ビッグデータに基づくエリア分散表現の加法構成性の分析と活用

田村 直樹, 浦野 健太, 米澤 拓郎, 河口 信夫

第107回MBL研究会     2023年5月

移動ビッグデータを用いた公共空間の価値評価手法

坂倉 波輝, 米澤 拓郎, 田村 直樹, 永田 吉輝, 庄子 和之, 山口 公平, 浦野 健太, 河口 信夫

第107回MBL研究会     2023年5月

IRIS: Interpretable Rubric-Informed Segmentation for Action Quality Assessment Open Access

Matsuyama H., Kawaguchi N., Lim B.Y.

International Conference on Intelligent User Interfaces, Proceedings IUI     頁： 368 - 378   2023年3月

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記述言語：英語   掲載種別：研究論文（学術雑誌）   出版者・発行元：International Conference on Intelligent User Interfaces, Proceedings IUI  

AI-driven Action Quality Assessment (AQA) of sports videos can mimic Olympic judges to help score performances as a second opinion or for training. However, these AI methods are uninterpretable and do not justify their scores, which is important for algorithmic accountability. Indeed, to account for their decisions, instead of scoring subjectively, sports judges use a consistent set of criteria - rubric - on multiple actions in each performance sequence. Therefore, we propose IRIS to perform Interpretable Rubric-Informed Segmentation on action sequences for AQA. We investigated IRIS for scoring videos of figure skating performance. IRIS predicts (1) action segments, (2) technical element score differences of each segment relative to base scores, (3) multiple program component scores, and (4) the summed final score. In a modeling study, we found that IRIS performs better than non-interpretable, state-of-the-art models. In a formative user study, practicing figure skaters agreed with the rubric-informed explanations, found them useful, and trusted AI judgments more. This work highlights the importance of using judgment rubrics to account for AI decisions.

DOI： 10.1145/3581641.3584048

Scopus

CrowdFlowTransformer: Capturing Spatio-Temporal Dependence for Forecasting Human Mobility 査読有り

Choya T., Tamura N., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023     頁： 496 - 501   2023年3月

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担当区分：最終著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）   出版者・発行元：2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2023  

Crowd flow forecasting is expected to have a wide range of applications such as human resource allocation, guidance design, marketing, disaster mitigation and congestion prediction for avoiding epidemic such as COVID-19. Crowd flow forecasting is challenging because it requires considering both the task of capturing the temporal dependency of data and capturing the spatial dependence. To address these challenges, in this paper, we propose a mechanism for referencing time-series features that are important for forecasting and incorporating graph convolution into Transformer, and we introduce CrowdFlowTransformer(CF-Transformer), a deep learning model based on Google's Transformer framework captures the Spatio-temporal dependency of time series. CF-Transformer captures the time series dependency by extracting important local time series from the past time series, inputting them to the decoder of Transformer, and encoding critical features into the model's input. We adapted CF-Transformer to a real-world crowd flow dataset. We evaluated it by comparing its forecasting accuracy with conventional models, and the results demonstrate that our model outperforms the conventional models.

DOI： 10.1109/PerComWorkshops56833.2023.10150301

Scopus