Faculty Profiles - KAWAGUCHI, Nobuo

Papers - KAWAGUCHI, Nobuo

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Fixture-aware Panoramic Ceiling Image Synthesis Using an Omnidirectional Camera Invited Reviewed

Daiki,Kohama, Yoshiteru,Nagata, Kazushige,Yasutake, Shin,Katayama, Kenta,Urano, Takuro,Yonezawa, Nobuo,Kawaguchi

Journal of Information Processing Vol. Vol.33 ( 2025 ) 2025.3

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

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 page： 98 - 105 2024.3

Language：English Publishing type：Research paper (scientific journal) Publisher：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

都市を対象とした大規模移動履歴に基づく疑似人流データ生成手法 Invited Reviewed

田村直樹, 浦野健太, 青木俊介, 米澤拓郎, 河口信夫

情報処理学会論文誌 Vol. 64 ( 1 ) page： 123 - 133 2023.1

ER-Chat: A Text-to-Text Open-Domain Dialogue Framework for Emotion Regulation Reviewed

Katayama Shin, Aoki Shunsuke, Yonezawa Takuro, Okoshi Tadashi, Nakazawa Jin, Kawaguchi Nobuo

IEEE TRANSACTIONS ON AFFECTIVE COMPUTING Vol. 13 ( 4 ) page： 2229 - 2237 2022.10

Authorship：Last author Language：English Publishing type：Research paper (scientific journal) Publisher：IEEE Transactions on Affective Computing

Emotions are essential for constructing social relationships between humans and interactive systems. Although emotional and empathetic dialogue generation methods have been proposed for dialogue systems, appropriate dialogue involves not only mirroring emotions and always being empathetic but also complex factors such as context. This paper proposes Emotion Regulation Chat (ER-Chat) as an end-to-end dialogue framework for emotion regulation. Emotion regulation is concerned with actions to approach appropriate emotional states. Learning appropriate emotion and intent when responding on the basis of the context of the dialogue enables the generation of more human-like dialogue. We conducted automatic and human evaluations to demonstrate the superiority of ER-Chat over the baseline system. The results show that inclusion of emotion and intent prediction mechanisms enable generation of dialogues with greater fluency, diversity, emotion awareness, and emotion appropriateness, which are greatly preferred by humans.

DOI： 10.1109/TAFFC.2022.3191973

Web of Science

Scopus

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

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

IEEE SENSORS JOURNAL Vol. 21 ( 22 ) page： 25437 - 25448 2021.11

Authorship：Last author Language：English Publishing type：Research paper (scientific journal) Publisher：IEEE Sensors Journal

Dance performance recognition methods have been investigated and shown various applications such as picture-pose evaluation and synchronizing foot timing and direction. However, detailed analysis and feedback are still missing. To provide them, understanding the performance by component level is necessary. Specifically, we formulate it as a dance-figure classification problem using three-dimensional body joints and wearable sensors. Our model is based on long short-term memory (LSTM) and includes the temporal and trajectory-wise structure that uses the trajectory information in a timestep and the temporal masking module. As a result, we achieved 93% accuracy with our proposed method, which is highly overwhelming the baseline result (84.7%) and very close to the accuracy of the experienced dancers (93.6%). We have made the dataset of ballroom dance performance dataset open to researchers to develop the activity recognition field further.

DOI： 10.1109/JSEN.2021.3098744

Web of Science

Scopus

大規模ユーザの滞在情報に基づくエリアの特徴付けとCOVID-19による影響分析 Reviewed

庄子和之, 青木俊介, 米澤拓郎, 河口信夫

情報処理学会論文誌 Vol. 62 page： 1644 - 1657 2021.10

Efficient Edge AI based Annotation and Detection Framework for Logistics Warehouses Reviewed

Yuki Mori, Yusuke Asai, Keisuke Higashiura, Shin Katayama, Kenta Urano, Takuro Yonezawa, Nobuo Kawaguchi

IEEE Consumer Communications & Networking Conference 2025 2025.1

Additive Compositionality in Urban Area Embeddings Based on Human Mobility Patterns

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

Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems page： 577 - 580 2024.10

Unveiling Human Attributes through Life Pattern Clustering using GPS Data Only

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

Proceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems page： 621 - 624 2024.10

Time-series Stay Frequency for Multi-City Next Location Prediction using Multiple BERTs Reviewed

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

32nd ACM SIGSPATIAL International Workshop on the Human Mobility Prediction Challenge, HuMob-Challenge 2024 page： 5 - 9 2024.10

自律移動ロボットを用いた人流計測のための探索経路生成 Invited Reviewed

下里浩昇, 片山晋, 浦野健太, 米澤拓郎, 河口信夫

情報処理学会論文誌 Vol. 65 page： 1511 - 1522 2024.10

倉庫内業務の量子アニーリングによる最適化とシミュレーションによる評価

瀧上昂希，福島悠人，浅井悠佑，片山晋，浦野健太，米澤拓郎，河口信夫

第81回UBI研究会 2024.2

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

Kazuyuki Shoji, Shunsuke Aoki, Takuro Yonezawa, Nobuo Kawaguchi

arxiv.org/abs/2401.10648v1 Vol. abs/2401.10648 2024

Poster: Sustainable Data Management Flow for Spatio-Temporal Datasets

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 page： 688 - 689 2024

Language：English Publishing type：Research paper (scientific journal) Publisher：MOBISYS 2024 - Proceedings of the 2024 22nd Annual International Conference on Mobile Systems, Applications and Services

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

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

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 page： 620 - 621 2024

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

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

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

DISTRIBUTED, AMBIENT AND PERVASIVE INTERACTIONS, PT I, DAPI 2024 Vol. 14718 page： 311 - 323 2024

Language：English Publishing type：Research paper (scientific journal) Publisher：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

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

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 page： 12 - 17 2024

Language：English Publishing type：Research paper (scientific journal) Publisher：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

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

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 page： 286 - 289 2024

Language：English Publishing type：Research paper (scientific journal) Publisher：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

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 page： 201 - 204 2024

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

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 page： 507 - 512 2024

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

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Papers - KAWAGUCHI, Nobuo