研究者詳細 - 米澤　拓郎

論文 - 米澤　拓郎

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NSP-BERT：滞在時間を考慮に入れた効率的なNext Stay予測手法査読有り

寺島青, 田村直樹, 庄子和之, 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(DICOMO2024)シンポジウム頁： 1531 - 1537 2024年6月

エッジAI向け物体検出モデル作成におけるアノテーション効率化手法査読有り

森裕輝, 浅井悠佑, 東浦圭亮, 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(DICOMO2024)シンポジウム頁： 292 - 301 2024年6月

効率と安全を考慮したコストマップを用いた人と協調する倉庫内配送ロボットナビゲーション査読有り

浅井悠佑, 片山晋, 浦野健太, 米澤拓郎, 河口信夫

情報処理学会論文誌 65 巻 ( 6 ) 頁： 1033 - 1048 2024年6月

スマートフォンを用いた歩行者自律航法のための水平加速度に基づいた歩き方の違いに頑健な進行方向推定査読有り

加納一馬，吉田拓人，浦野健太，米澤拓郎，河口信夫

情報処理学会論文誌 65 巻 ( 6 ) 頁： 1001 - 1017 2024年6月

プライバシフリーな通過情報を用いた大規模施設における移動経路推定手法査読有り

永田吉輝, 浦野健太, 米澤拓郎, 河口信夫

情報処理学会論文誌 65 巻 ( 6 ) 頁： 1018 - 1032 2024年6月

BERTに基づく都市における移動エリア予測手法の提案

寺島青, 田村直樹, 庄子和之, 片山晋, 浦野健太, 米澤拓郎, 河口信夫

第119回MBL研究会 2024年5月

SafariCast:サファリ地域における動物のストレスを考慮した位置情報共有システム

志村魁哉, 片山晋, 浦野健太, Emanuel Leleito, 米澤拓郎, 河口信夫

第82回UBI研究会 2024年5月

量子アニーリングとブラックボックス最適化を用いた倉庫内業務最適化

髙木魁利，瀧上昂希，片山晋，浦野健太，米澤拓郎，河口信夫

第82回UBI研究会 2024年5月

Theme 4: Infrastructure and Service Resilience for Smart Society 査読有り

Stylios, C; Yonezawa, T

ERCIM NEWS ( 136 ) 頁： 10 - 10 2024年1月

Towards a Real-Time and Energy-Efficient Edge AI Camera Architecture in Mega Warehouse Environment 査読有り

Asai Y., Mori Y., Higashiura K., Yokoyama K., Katayama S., Urano K., Yonezawa T., Kawaguchi N.

Proceedings - 2024 IEEE 3rd Real-Time and Intelligent Edge Computing Workshop, RAGE 2024 頁： 12 - 17 2024年

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：Proceedings - 2024 IEEE 3rd Real-Time and Intelligent Edge Computing Workshop, RAGE 2024

In response to the exponential growth of e-commerce, our paper addresses the transformation of warehouse operations towards mega warehouses, necessitating advanced digitalization. We focus on the integration and optimization of edge AI technologies to enhance operational efficiency, accuracy, and timeliness in logistic warehouses. We propose a novel edge AI architecture tailored to the processes of warehouse operations ensuring that digitalization aligns with operational workflows. Utilizing a real-world warehouse equipped with over 60 cameras as a testbed, we demonstrate the practical application and benefits of edge computing in logistics. Our experiments have shown significant potential improvements in energy efficiency and timeliness, crucial metrics for the successful integration of edge AI technologies in warehouses.

DOI： 10.1109/RAGE62451.2024.00010

Scopus

Balancing Excitement and Environmental Conservation in Information Dissemination for Safari Game Drives 査読有り

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

DISTRIBUTED, AMBIENT AND PERVASIVE INTERACTIONS, PT I, DAPI 2024 14718 巻頁： 311 - 323 2024年

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

In the context of Kenyan Safari Game Drives, which traditionally rely on visual scouting and intermittent communication, challenges arise regarding the effectiveness of animal detection and environmental conservation. Consequently, animals experience stress, and tourists encounter difficulties in observation due to obstruction by other visitors. Addressing these challenges involves maintaining animal welfare while enhancing tourist satisfaction. To revitalize post-pandemic tourism and enrich safari experiences, this study proposes a wildlife spotting and sharing system. The proposed method integrates wildlife detection and sharing technologies guided by three core principles: preserving encounter serendipity, regulating information access, and promoting environmental conservation. The system architecture incorporates sensors, GPS, and tablet terminals to facilitate real-time data collection, animal identification, and information dissemination. This approach aims to foster an engaging, efficient, and environmentally conscious wildlife spotting and sharing experience, potentially establishing a model for sustainable wildlife tourism in comparable wildlife-rich regions.

DOI： 10.1007/978-3-031-59988-0_19

Web of Science

Scopus

Demo: Assisting System for Creating Ceiling Plan Using a Video from a Smatrphone 査読有り

Kohama, D; Nagata, Y; Yasutake, K; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

PROCEEDINGS OF THE 2024 THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS AND SERVICES, MOBISYS 2024 頁： 620 - 621 2024年

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：MOBISYS 2024 - Proceedings of the 2024 22nd Annual International Conference on Mobile Systems, Applications and Services

We present an assisting system for creating a ceiling plan. Conventional methods of creating a ceiling plan are time-consuming and high-cost. Our system requires only two inputs from a user and outputs the panoramic ceiling image that shows the whole ceiling surface. The system detects the ceiling fixtures and depicts them seamlessly for a reliable resulting image. We confirmed the possibility of assisting in creating a ceiling plan with our system through the experiment.

DOI： 10.1145/3643832.3661847

Web of Science

Scopus

Poster: Sustainable Data Management Flow for Spatio-Temporal Datasets 査読有り

Nagata, Y; Kohama, D; Watanabe, Y; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

PROCEEDINGS OF THE 2024 THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS, APPLICATIONS AND SERVICES, MOBISYS 2024 頁： 688 - 689 2024年

Spatio-temporal data is utilized in various fields, but its scale is continuously growing, leading to significant labor and costs in storage and processing. Therefore, the value that can be derived from spatio-temporal data is diluted due to management costs. We propose a new data management flow using various metadata and common programs for spatio-temporal data utilization. Traditionally, various spatio-temporal data processing have been implemented and processed according to each spatio-temporal data. We defined spatio-temporal data structure metadata and performed data processing based on metadata using a common data processing program. Furthermore, we automated the generation of data structure metadata by combining our data skeleton recognition method and generative AI model. Using this flow, we expect to improve the sustainability of utilizing spatio-temporal data.

DOI： 10.1145/3643832.3661423

Web of Science

Scopus

Semi-Automated Framework for Digitalizing Multi-Product Warehouses with Large Scale Camera Arrays 査読有り

Higashiura, K; Yokoyama, K; Asai, Y; Shimosato, H; Kano, K; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

2024 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS, PERCOM 頁： 98 - 105 2024年

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：2024 IEEE International Conference on Pervasive Computing and Communications, PerCom 2024

As global demand for logistics continues to grow, optimizing the automation and efficiency of distribution warehouse operations is of paramount importance. Digitalizing warehouse environments, which refers to the process of sensing the physical space and extracting meaningful information from the obtained data, offers a promising solution to this challenge. However, converting raw warehouse data, such as video footage captured inside the warehouse, into actionable metadata (e.g., tracking the movement paths of workers and products or analyzing the usage patterns of different warehouse locations) often necessitates significant human intervention. The rise of machine learning further complicates this, as it requires the manual preparation of extensive training datasets. In this paper, we introduce a framework that semi-automates the digitalization process in complex warehouse settings. This framework employs dense optical flow and representation learning to autonomously segment warehouse objects and cluster similar objects, thereby substantially cutting down on annotation costs. To evaluate our approach, we constructed a large-scale data collection platform with over 60 fixed cameras in a real-world logistics warehouse, and the video data from this platform was then applied to our framework. Our evaluations indicate that our method markedly reduces both the time and resources required for warehouse digitalization using the captured video data.

DOI： 10.1109/PERCOM59722.2024.10494498

Web of Science

Scopus

Area Modeling using Stay Information for Large-Scale Users and Analysis for Influence of COVID-19. 査読有り

Kazuyuki Shoji, Shunsuke Aoki 0001, Takuro Yonezawa, Nobuo Kawaguchi

CoRR abs/2401.10648 巻 2024年

Composite Image Generation Using Labeled Segments for Pattern-Rich Dataset without Unannotated Target 査読有り

Kano, K; Mori, Y; Higashiura, K; Hossain, T; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

COMPANION OF THE 2024 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING, UBICOMP COMPANION 2024 頁： 507 - 512 2024年

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：UbiComp Companion 2024 - Companion of the 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing

Although object detection technology using cameras offers potential for various applications, it incurs dataset creation costs to train new models where general-purpose models are ineffective, such as in industrial settings. We have previously developed a semi-automated annotation framework that employs optical flow and representation learning techniques to reduce human effort significantly. However, it was likely to cause unintended annotation omissions and mistakes compared to manual annotation. In this study, we propose a composite image generation approach to create omission-free and pattern-rich datasets. The proposed method synthesizes natural-looking images without unannotated targets by placing labeled foreground segments at their original positions on targetless background frames collected with the same fixed-point cameras. Evaluation with video footage in a logistics warehouse confirmed that improved dataset reliability led to higher model performance.

DOI： 10.1145/3675094.3678447

Web of Science

Scopus

Enhancing Group Telepresence Interaction through Seamless Inverse Panorama Projection on Spherical Display 査読有り

Hayashida, N; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

COMPANION OF THE 2024 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING, UBICOMP COMPANION 2024 頁： 286 - 289 2024年

In recent years, advancements in telepresence technology have made remote communication and collaboration easier. MetaPo is a system that uses spherical displays to seamlessly integrate physical and digital interactions. However, conventional inverse panorama techniques face challenges such as image seams, coverage issues, and overlapping displays. To address these challenges, this study proposes an inverse panorama technique based on coordinate transformation, enhancing visual continuity and user experience. Additionally, evaluation methods necessary to demonstrate the effectiveness of the proposed method in improving the quality of remote communication have been devised. This research provides a novel solution to challenges in spherical display technology and paves the way for more immersive telepresence experiences.

DOI： 10.1145/3675094.3678369

Web of Science

Scopus

Demonstration:Remote 3D Scanning with VR and Robotic Arm 査読有り

Usami, R; Watanabe, K; Gushi, Y; Tsutsui, S; Watanabe, Y; Kano, K; Aikawa, Y; Shimura, K; Hayashida, N; Urano, K; Yonezawa, T; Kawaguchi, N

COMPANION OF THE 2024 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING, UBICOMP COMPANION 2024 頁： 201 - 204 2024年

Although VR headsets have gained widespread acceptance, their potential for real-world actuation remains underexplored. We propose a system that allows to work in VR space using a robotic arm and VR headset, focusing on 3D scanning as the task. The robotic arm is equipped with an RGB-D camera to achieve remote 3D scanning. This system enables immersive remote work and enhances the link between real space and VR space by reproducing the real objects into the VR space.

DOI： 10.1145/3675094.3677548

Web of Science

Scopus

Wildlife Spotting and Sharing System for Kenyan Safari Game Drives 査読有り

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

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

記述言語：日本語掲載種別：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 Interaction for Group Telepresence with MetaPo 査読有り

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

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

記述言語：日本語掲載種別：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

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