研究者詳細 - 米澤　拓郎

論文 - 米澤　拓郎

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BERTに基づく都市における移動エリア予測手法の提案 Open Access

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 Open Access

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 Open Access

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

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 2024年3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 System for Omni-directional Interaction by Multiple Users 査読有り

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

ACM International Conference Proceeding Series 頁： 295 - 299 2024年3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

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

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 2024年3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

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

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

Web of Science

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 Open Access

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（国際会議プロシーディングス）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

Open Access

Web of Science

Scopus

その他リンク： https://dblp.uni-trier.de/db/conf/mobisys/mobisys2024.html#KohamaNYKUYK24

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

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

Open Access

Web of Science

Scopus

その他リンク： https://dblp.uni-trier.de/rec/conf/mobisys/2024

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

Unveiling Human Attributes through Life Pattern Clustering using GPS Data Only 査読有り

Shoji, K; Terashima, H; Tamura, N; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

32ND ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS, ACM SIGSPATIAL 2024 頁： 621 - 624 2024年

記述言語：日本語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：32nd ACM Sigspatial International Conference on Advances in Geographic Information Systems ACM Sigspatial 2024

Clustering people by their life patterns is valuable in government and business fields. Existing studies often rely on semantic data such as Point of Interest or stay purpose. However, they have the problem that obtaining large datasets is difficult due to the need for annotation work. Some studies try to use only location data. However, they do not reveal the semantics of the area where visitors stay because they only label visited areas by significance according to duration and frequency of stay. In this paper, we propose a framework, LPSeL, for clustering people’s Life Patterns at a Semantic Level using only raw GPS location data. LPSeL is based on the idea that analyzing human mobility first requires understanding urban space. Therefore, it begins with area modeling, which models areas in a city based on people’s activities. Then, treating human mobility as a sequence of area representations makes it possible to model individuals by semantic-level characteristics of their life patterns. We showed that LPSeL is capable of estimating people’s attributes from their life patterns using a real-world dataset consisting of GPS data collected from tens of thousands of smartphone users.

DOI： 10.1145/3678717.3691309

Web of Science

Scopus

Time-series Stay Frequency for Multi-City Next Location Prediction using Multiple BERTs 査読有り

Terashima, H; Takagi, S; Tamura, N; Shoji, K; Hossain, T; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

2ND ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON THE HUMAN MOBILITY PREDICTION CHALLENGE, HUMOB-CHALLENGE 2024 頁： 5 - 9 2024年

記述言語：日本語掲載種別：研究論文（国際会議プロシーディングス）出版者・発行元：2nd ACM Sigspatial International Workshop on the Human Mobility Prediction Challenge Humob Challenge 2024

Human Mobility Prediction Challenge 2024 was organized to compare human future movement prediction methods using a unified dataset. The challenge focuses on human movement prediction in multiple cities with varying numbers of users. Many existing movement prediction methods train deep learning models using large-scale movement histories from cities and make predictions. While cities with large users have sufficient training data, smaller cities with fewer users may face challenges due to insufficient data, raising concerns about lower prediction accuracy. Additionally, it is difficult to treat stay locations between different cities’ movement histories due to differences in spatial area arrangement, making it challenging to share data across cities. To address this issue, we propose human movement prediction method that utilizes time-series stay frequency patterns, which can be commonly applied across different cities. This method demonstrated superiority in predicting movements in cities with fewer users compared to models trained and predicted using only the movement histories of the target city. Furthermore, the method achieved top 10 prediction accuracy in HuMob Challenge 2024.

DOI： 10.1145/3681771.3699909

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

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

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

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

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

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

Open Access

Web of Science

Scopus

Additive Compositionality in Urban Area Embeddings Based on Human Mobility Patterns 査読有り

Tamura, N; Terashima, H; Shoji, K; Katayama, S; Urano, K; Yonezawa, T; Kawaguchi, N

32ND ACM SIGSPATIAL INTERNATIONAL CONFERENCE ON ADVANCES IN GEOGRAPHIC INFORMATION SYSTEMS, ACM SIGSPATIAL 2024 頁： 577 - 580 2024年

Understanding the characteristics of various urban areas is crucial for applications such as urban planning, tourism policies, market analysis, and infection control. Techniques for embedding areas as vectors in a latent space based on human mobility patterns are actively researched. Many of these area embedding methods define areas as points, grids, or polygons on a geospatial plane and then embed them. However, existing methods do not allow for mutual transformation between these forms and sizes after the initial embedding. Additionally, if the characteristics of an area change due to events such as the opening of new buildings, re-embedding is necessary. Meanwhile, the Word2Vec technique, a representative word embedding method, has a property called additive compositionality. This property allows for the arithmetic operation of word meanings through the arithmetic operations of word embeddings. In this paper, we propose a method to apply this property to existing area embedding techniques, leveraging it for practical tasks such as area shape transformation and searching for areas with trends change.

DOI： 10.1145/3678717.3691279

Web of Science

Scopus

OpenUAS: Embeddings of Cities in Japan with Anchor Data for Cross-city Analysis of Area Usage Patterns. 査読有り

Naoki Tamura, Kazuyuki Shoji, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

CoRR abs/2407.19872 巻 2024年

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論文 - 米澤 拓郎

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論文 - 米澤　拓郎