研究者詳細 - 藤井　慶輔

論文 - 藤井　慶輔

分割表示 105 件中 81 - 100 件目／全件表示 >>

Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: An application to rugby union 査読有り

Rory Bunker, Keisuke Fujii, Hiroyuki Hanada, Ichiro Takeuchi

PLOS ONE 16 巻 ( 9 ) 頁： e0256329 - e0256329 2021年9月

Flexible prediction of opponent motion with internal representation in interception behavior 査読有り

Kazushi Tsutsui, Keisuke Fujii, Kazutoshi Kudo, Kazuya Takeda

Biological Cybernetics 2021年8月

Understanding Others' Roles Based on Perspective Taking in Coordinated Group Behavior 査読有り

Jun Ichikawa, Keisuke Fujii

Proceedings of the Annual Meeting of the Cognitive Science Society 43 巻頁： 1285 - 1291 2021年8月

Extraction of swing motion contributing to prediction of shuttle drop position in badminton 査読有り

Tatsuya Yoshikawa, Kazushi Tsutsui, Kazuya Takeda, Keisuke Fujii

30th International Joint Conference on Artificial Intelligence (IJCAI-21) workshop on AI for Sports Analytics (AISA) 2021年8月

なぞり課題を用いた運動協調における役割の検討査読有り

市川淳, 藤井慶輔

認知科学 28 巻 ( 1 ) 頁： 170 - 173 2021年3月

Quantitative analysis of spontaneous sociality in children's group behavior during nursery activity 査読有り国際誌

Ichikawa Jun, Fujii Keisuke, Nagai Takayuki, Omori Takashi, Oka Natsuki

PLOS ONE 16 巻 ( 2 ) 頁： e0246041 2021年2月

Trajectory prediction with imitation learning reflecting defensive evaluation in team sports 査読有り

Teranishi M.

2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020 頁： 124 - 125 2020年12月

Cognition and interpersonal coordination of patients with schizophrenia who have sports habits 査読有り国際誌

Fujii Keisuke, Yoshihara Yujiro, Matsumoto Yukiko, Tose Keima, Takeuchi Hideaki, Isobe Masanori, Mizuta Hiroto, Maniwa Daisuke, Okamura Takehiko, Murai Toshiya, Kawahara Yoshinobu, Takahashi Hidehiko

PLOS ONE 15 巻 ( 11 ) 頁： e0241863 2020年11月

Succinct Trit-array Trie for Scalable Trajectory Similarity Search 査読有り

Kanda S.

GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems 頁： 518 - 529 2020年11月

協調に関する議論に向けたアプローチの提案：集団運動からみる他者の行動予測と適応査読有り

市川淳, 藤井慶輔

認知科学 27 巻 ( 3 ) 頁： 377 - 385 2020年9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：日本認知科学会

<p>In this paper, we propose a research approach that is used in cognitive science to investigate more complex coordination mechanisms between three or more people. That is, we propose an approach that uses position data to quantitatively analyze group behavior and to link these characteristics with the cognition of anticipating others' behaviors. It is important for coordination to anticipate others' behaviors and to adapt one's own body movement to others based on anticipation. We highlight previous studies on problem solving and learning in cognitive science which have investigated interaction processes from verbal protocols during task implementation and indicated the importance of understanding others' perspectives. Additionally, recent cognitive models of estimating others' intentions and anticipating others' behaviors during interactions using non-verbal information such as eye movement, posture, and gesture, have been investigated. Considering these previous studies, we focus on group behavior and propose to apply the new approach mentioned above to discuss a mechanism of more complex coordination. We also refer to some studies of biological group behaviors in biology, artificial life, and sports science, and demonstrate a potential issue that such papers did not focus on the cognition related to coordinative group behaviors. This paper illustrates an example of discussing interactions with others, to which the new approach is applied. Our previous study here analyzed children's group behavior during nursery activities using position data and linked these characteristics with the cognitive development of anticipating others' behaviors based on spontaneous sociality. However, it is difficult to investigate some details of group behavior due to the limitation of field measurement, for example, the accuracy of a child's anticipation and whether a child moved based upon anticipation. In future work, it is important to analyze controlled group behavior and to indicate accuracy of individuals' anticipation from movement data to solve these problems.</p>

DOI： 10.11225/cs.2020.026

CiNii Research

COGNITION AND SOCIAL BEHAVIORS IN SPORTS FOR PATIENTS WITH SCHIZOPHRENIA ENGAGED IN SPORTS HABITS 査読有り

Yoshihara Yujiro, Fujii Keisuke, Murai Toshiya, Takahashi Hidehiko

SCHIZOPHRENIA BULLETIN 46 巻頁： S128 - S128 2020年4月

Practice Motions Performed During Preperformance Preparation Drive the Actual Motion of Golf Putting 査読有り

Hasegawa Yumiko, Miura Akito, Fujii Keisuke

FRONTIERS IN PSYCHOLOGY 11 巻頁： Article 513 2020年3月

Practice Motions Performed During Preperformance Preparation Drive the Actual Motion of Golf Putting 査読有り

Yumiko Hasegawa, Akito Miura, Keisuke Fujii

Frontier in Psychology 11 巻 ( 513 ) 頁： https://doi.org/10.3389/fpsyg.2020.00513 2020年3月

Dynamic mode decomposition via dictionary learning for foreground modeling in videos 査読有り

Israr Ul Haq, Keisuke Fujii, Yoshinobu Kawahara

15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP'20) 5 巻 ( - ) 頁： 476-483 2020年3月

Physically-interpretable classification of network dynamics for complex collective motions 査読有り

Keisuke Fujii, Naoya Takeishi, Motokazu Hojo, Yuki Inaba, Yoshinobu Kawahara

Scientific Reports 10 巻 ( 3005 ) 頁： https://doi.org/10.1038/s41598-020-58064-w 2020年2月

協調に関する議論に向けたアプローチの提案－集団運動からみる他者の行動予測と適応－査読有り

市川淳, 藤井慶輔

認知科学 27 巻 ( 3 ) 頁： xx - xx 2020年

高速かつ省メモリな軌跡類似検索のための簡潔トライ索引査読有り

神田峻介, 竹内孝, 藤井慶輔, 田部井靖生

人工知能学会全国大会論文集 2020 巻 ( 0 ) 頁： 2C4OS7a01 - 2C4OS7a01 2020年

掲載種別：研究論文（学術雑誌）出版者・発行元：一般社団法人人工知能学会

<p>本稿では、大規模な軌跡データに対する効率的な類似検索手法を提案する。本手法はLocality Sensitive HashingとTrie木を活用し高速な類似検索を実現する。高いメモリ効率を実現するために、冗長なTrie木の節点を削減する手法を提案する。さらに、三進数配列を用いたTrie木の簡潔表現であるSuccinct Trit-Array Trieを提案する。大規模な実データを用いた実験において、既存手法と比べて提案手法は検索速度とメモリ効率に関して高い性能を示した。</p>

DOI： 10.11517/pjsai.JSAI2020.0_2C4OS7a01

「現場と研究の橋渡し」（ 2 ）にあたって

藤井慶輔, 永田直也

バスケットボール研究 6 巻 ( 0 ) 頁： 1 - 2 2020年

Dynamic mode decomposition via dictionary learning for foreground modeling in videos 査読有り

Israr Ul Haq, Keisuke Fujii, Yoshinobu Kawahara

VISIGRAPP 2020 - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications 5 巻頁： 476 - 483 2020年

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：SciTePress

Accurate extraction of foregrounds in videos is one of the challenging problems in computer vision. In this study, we propose dynamic mode decomposition via dictionary learning (dl-DMD), which is applied to extract moving objects by separating the sequence of video frames into foreground and background information with a dictionary learned using block patches on the video frames. Dynamic mode decomposition (DMD) decomposes spatiotemporal data into spatial modes, each of whose temporal behavior is characterized by a single frequency and growth/decay rate and is applicable to split a video into foregrounds and the background when applying it to a video. And, in dl-DMD, DMD is applied on coefficient matrices estimated over a learned dictionary, which enables accurate estimation of dynamical information in videos. Due to this scheme, dl-DMD can analyze the dynamics of respective regions in a video based on estimated amplitudes and temporal evolution over patches. The results on synthetic data exhibit that dl-DMD outperforms the standard DMD and compressed DMD (cDMD) based methods. Also, the results of an empirical performance evaluation in the case of foreground extraction from videos using publicly available dataset demonstrates the effectiveness of the proposed dl-DMD algorithm and achieves a performance that is comparable to that of the state-of-the-art techniques in foreground extraction tasks.

Scopus

researchmap

Motor control of practice and actual strokes by professional and amateur golfers differ but feature a distance-dependent control strategy 査読有り国際誌

Yumiko Hasegawa, Keisuke Fujii, Akito Miura, Keiko Yokoyama, Yuji Yamamoto

European Journal of Sport Science 19 巻 ( 9 ) 頁： 1204 - 1213 2019年10月

　前のページ - 次のページ　

<藤井 慶輔>

論文 - 藤井 慶輔

<藤井　慶輔>

論文 - 藤井　慶輔