研究者詳細 - 米澤　拓郎

論文 - 米澤　拓郎

分割表示 280 件中 1 - 20 件目／全件表示 >>

VR180 遠隔ロボットアームシステムにおける操作支援のための情報提示手法の検討

筒井秀斗, 渡邉企章, 宇佐美龍斗, 具志祐希, 渡辺圭貴, 林田望海, 志村魁哉, 浦野健太, 米澤拓郎, 河口信夫

第85回UBI研究会 2025年2月

Efficient Edge AI based Annotation and Detection Framework for Logistics Warehouses 査読有り国際誌

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

IEEE Consumer Communications & Networking Conference 2025 2025年1月

Fixture-aware Panoramic Ceiling Image Synthesis Using an Omnidirectional Camera 査読有り

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

Journal of Information Processing 33 巻 ( 0 ) 頁： 245 - 258 2025年

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Information Processing Society of Japan

<p>The manual creation of a ceiling plan consumes many human resources to confirm the current state of existing buildings for renovation. Identifying the positions and the types of existing fixtures is crucial for drawing a ceiling plan. Therefore, to assist in drawing a ceiling plan, an efficient method that generates a reliable photorealistic whole ceiling surface image is essential. We present a method of fixture-aware panoramic ceiling image synthesis using an omnidirectional camera. A fixture-aware panoramic ceiling image is a photorealistic image that depicts the whole ceiling surface and no seams on ceiling fixtures for its reliability regarding assistance in drawing a ceiling plan. The proposed method is remarkably effortless because it requires the users to work only 2 procedures for synthesizing the image, 1) shooting an omnidirectional video underneath the ceiling and 2) fixture measurement in the image. In the experiment, we evaluated the resulting image for the positional and shape accuracy of the ceiling fixtures and the time efficiency of the measurement. Our proposed method demonstrated a positional accuracy of 2.25 times higher, a shape accuracy of 5.87 times higher, and a time efficiency of the measurement 11.09 times higher than the baseline.</p>

DOI： 10.2197/ipsjjip.33.245

CiNii Research

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12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：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

Scopus

共通潜在空間を介した多様な都市データのクロスモーダル分析手法

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

第84回UBI研究会 2024年11月

時系列滞在頻度傾向と移動傾向を組み合わせた移動先予測手法

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

第84回UBI研究会 2024年11月

EngagedSync ： MR 共有空間内ユーザの相互状況理解向上のための適応的な周辺環境情報抽出・転送システム

志村魁哉, 加納一馬, Tahera Hossain, 片山晋, 浦野健太, 米澤拓郎, 河口信夫

第84回UBI研究会 2024年11月

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10月

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

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

Scopus

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10月

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

Scopus

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査読有り

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 65 巻 ( 10 ) 頁： 1511 - 1522 2024年10月

DiverCityMeter: GPSデータのみを用いた生活パターン多様性から見る COVID-19 の影響分析に関する研究

庄子和之，寺島青，田村直樹，片山晋，浦野健太，米澤拓郎，河口信夫

第112回MBL研究会 2024年9月

遠隔MRロボットアーム制御によるスマートな3Dスキャンシステム

宇佐美龍斗、渡邉企章、具志祐希、筒井秀斗、渡辺圭貴、加納一馬、相川雄也、志村魁哉、林田望海、浦野健太、米澤拓郎、河口信夫

第29回日本バーチャルリアリティ学会大会 2024年9月

スマートフォン・全方位カメラを用いた作業効率化のための半自動天伏図作成システム

小濱大輝，永田吉輝，安武和成，酒見和幸，片山晋，浦野健太，米澤拓郎，河口信夫

令和6年度空気調和・衛生工学会大会 2024年9月

Autoware-in-Forest: 森林環境における丸太運搬フォワーダの自動走行

浦野健太, 米澤拓郎, 河口信夫

第42回日本ロボット学会学術講演会（RSJ2024） 2024年9月

3次元点群解析に基づくロボット移動可能領域の半自動認識手法

相川雄也，片山晋，浦野健太，米澤拓郎，河口信夫

第42回日本ロボット学会学術講演会（RSJ2024） 2024年9月

エッジ音声処理とCAN通信を用いた多数接続可能な発話方向推定システム

市川　直人，加納　一馬，永田　吉輝，片山　晋，浦野　健太，米澤　拓郎，河口　信夫

電気・電子・情報関係学会東海支部連合大会 2024年8月

マルチカメラによるオクルージョン回避を用いた荷物置き場の占有状況検出

具志祐希，加納一馬，片山晋，浦野健太, 米澤拓郎, 河口信夫

電気・電子・情報関係学会東海支部連合大会 2024年8月

物流倉庫におけるスマートフォンを用いた作業者のタスク認識

渡邊企章，加納一馬，片山晋，浦野健太，米澤拓郎，河口信夫

電気・電子・情報関係学会東海支部連合大会 2024年8月

天伏図自動復元のための設備位置・形状アライメント手法

小濱大輝，永田吉輝，安武和成，片山晋，浦野健太，米澤拓郎，河口信夫

第42回電気設備学会全国大会 2024年8月

アノテーションロスを克服するラベル付き画像セグメントの合成によるデータ拡張

加納一馬，森裕輝，東浦圭亮，Tahera HOSSAIN，片山晋，浦野健太，米澤拓郎，河口信夫

画像電子学会年次大会（MCC2024） 2024年8月

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