Updated on 2024/02/01

写真a

 
OKUSA Kosuke
 
Organization
Faculty of Science and Engineering Associate Professor
Other responsible organization
Data Science for Business Innovation Course of Graduate School of Science and Engineering, Master's Program
Data Science for Business Innovation Course of Graduate School of Science and Engineering, Doctoral Program
Profile

機械学習や統計モデリングに関する知見をセンサデータ解析技術へ展開することに興味を持ち研究をしています。近年では「独居老人の見守りシステム開発」や「屋内型位置推定技術の開発」に興味があります。また、企業との共同研究としてセンサデータを用いたスマートファクトリー実現に関する研究も行っています。

External link

Degree

  • 博士(工学) ( 中央大学 )

  • 修士(工学) ( 中央大学 )

Education

  • 2012.3
     

    Chuo University   Graduate School, Division of Science and Engineering   doctor course   completed

  • 2009.3
     

    Chuo University   Graduate School, Division of Science and Engineering   master course   completed

  • 2008.3
     

    Chuo University   Graduate School, Division of Science and Engineering   others   others

  • 2007.3
     

    Chuo University   Faculty of Science and Engineering   graduated

Research History

  • 2022.4 -  

    中央大学理工学部准教授   Research Associate

  • 2020.10 - 2022.3

    中央大学研究開発機構機構客員准教授

  • 2020.4 - 2022.3

    横浜市立大学データサイエンス学部准教授

  • 2020.4 -  

    九州大学応用生理人類学研究センター 学外協力研究員

  • 2016.4 - 2020.3

    福岡女子大学国際文理学部非常勤講師

  • 2014.4 - 2020.3

    九州大学大学院芸術工学研究院コミュニケーションデザイン科学部門助教

  • 2013.4 - 2014.3

    法政大学経営学部非常勤講師

  • 2012.4 - 2014.3

    中央大学理工学部助教   Faculty of Science and Engineering

  • 2013.4 -  

    ~ 法政大学兼任講師

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Professional Memberships

  • 日本計算機統計学会

  • 電子情報通信学会

  • 日本統計学会

  • IEEE Electron Devices Society

  • 日本分類学会

  • Association for Computing Machinery

  • 応用統計学会

  • 日本生理人類学会

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Research Interests

  • センサデータ解析

  • 統計

  • 機械学習

  • 計算機統計学

Research Areas

  • Informatics / Theory of informatics  / Sensing Data Analysis

  • Informatics / Theory of informatics  / Computational Statistics

  • Informatics / Statistical science  / 統計科学

Papers

  • Prediction of the number of defects in image sensors by VM using equipment QC data Reviewed

    Toshiya Okazaki, Kosuke Okusa, Kyo Yoshida

    IEEE Transactions on Semiconductor Manufacturing   32 ( 4 )   434 - 437   2019.9

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  • Estimates for the Spatial Locations of the Indoor Objects by Using Radial Extreme Value Weibull Distribution Reviewed

    Kosuke Okusa, Toshinari Kamakura

    IAENG Transactions on Engineering Sciences   2019   59 - 70   2019.6

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  • A Simulation Study for Performance Validate of Indoor Location Estimation based on the Radial Weibull/Extreme-Value Weibull Distribution Reviewed

    Kosuke Okusa, Toshinari Kamakura

    International Journal of Applied Mathematics   48 ( 2 )   111 - 117   2018.12

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  • 複数業務を行う窓口のサービス時間に着目した平均待ち時間の改善に関する研究 Reviewed

    永沼暁, 大草孝介

    計算機統計学   30 ( 1 )   43 - 50   2018.11

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  • マイクロ波ドップラーセンサを用いたモデルベースの転倒状態推定に関する研究 Reviewed

    永沼暁, 大草孝介

    計算機統計学   30 ( 1 )   17 - 30   2018.11

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  • A Simulation Study on Performance Validation of Indoor Location Estimation Based on the Radial Positive Distribution. Reviewed

    Kosuke Okusa, Toshinari Kamakura

    IAENG Transaction of Engineering Technologies   2017   89 - 100   2017.8

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  • 日本のプロ・オーケストラのプログラミングに影響を及ぼす要因 –統計分析を通じて- Reviewed

    西田紘子, 大草孝介

    日本文化政策学会   10   44 - 59   2017.5

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  • マイクロ波ドップラーセンサを用いた転倒動作のモデリングに関する研究

    永沼 暁, 大草 孝介

    日本計算機統計学会大会論文集   30   13 - 16   2016

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    DOI: 10.20551/jscstaikai.30.0_13

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  • Young and elderly, normal and pathological gait analysis using frontal view gait video data based on the statistical registration of spatiotemporal relationship

    Kosuke Okusa, Toshinari Kamakura

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   9741   668 - 678   2016

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Springer Verlag  

    We study the problem of analyzing and classifying frontal view gait video data. In this study, we focus on the shape scale changing in the frontal view human gait, we estimate scale parameters using the statistical registration and modeling on a video data. To demonstrate the effectiveness of our method, we apply our model to young and elderly, normal and pathological gait analysis. As a result, our model shows good performance for the scale estimation and gait analysis.

    DOI: 10.1007/978-3-319-40093-8_66

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  • A STUDY ON RECOMMENDATION SYSTEM BASED ON THE CUSTOMER'S INTEREST AND PURCHASE INDIVIDUALITY

    大草 孝介, 阿部 興, 榎本 大起, 桑原 洋祐, 森 健人, 加田 拓磨, 佐藤 のぞみ, 黒田 淑恵, 長 亜沙美, 猿田 将英, 沖原 史章, 露崎 博之, 高須 靖子, 勝 裕周, 吉田 敦, 吉田 啓悟, 鎌倉 稔成

    計算機統計学 = Bulletin of the Computational Statistics of Japan   29 ( 1 )   49 - 56   2016

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    Language:Japanese   Publisher:日本計算機統計学会  

    DOI: 10.20551/jscswabun.29.1_49

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  • Indoor Location Estimation based on the RSS method using Radial Log-normal Distribution

    Kosuke Okusa, Toshinari Kamakura

    2015 16TH IEEE INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND INFORMATICS (CINTI)   29 - 34   2015

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:IEEE  

    We study the problem of analyzing indoor location estimation by statistical radial distribution model. In this study, we suppose the observed distance data between transmitter and receiver as a radial log-normal distribution. We estimate the subject's location using marginal likelihoods of radial log-normal distribution. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the accuracy of location estimation of static case and dynamic case. In static experiment, subject is stationary state in some places in the chamber. This experiment is able to measure the precise performance of proposed method. In dynamic experiment, subject is move around in the chamber. This experiment is able to measure the suitability for practical use of proposed method. As a result, our method shows high accuracy for the static case indoor spatial location estimation.

    DOI: 10.1109/CINTI.2015.7382938

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  • DESIGN OF RECOMMENDATION SYSTEM FOR REAL-ESTATE E-COMMERCE SITE BASED ON THE CO-OCCURRENCE RELATION ANALYSIS OF SEARCH CRITERION

    Okusa Kosuke, Abe Kou, Naito Takaya, Yamaguchi Naoto, Kada Takuma, Kuroda Yoshie, Sato Nozomi, Hidaka Asuka, Mori Kento, Kamakura Toshinari

    Bulletin of the Computational Statistics of Japan   28 ( 2 )   147 - 154   2015

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    We present the design of recommendation system for real-estate e-commerce site based on the co-occurrence relation analysis of search criterion. A study on design of recommendation system is very important role in the field of e-commerce business. In this paper, We focus on the search criterion in the e-commerce site. Assuming that each search criterion have implicit relationship. We estimate the degree of association between each search criterions using zero-inflated beta distribution. As a result, our method shows good performance in the real-estate e-commerce site.

    DOI: 10.20551/jscswabun.28.2_147

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  • Indoor Location Estimation based on the Statistical Spatial Modeling and Radial Distributions

    Kosuke Okusa, Toshinari Kamakura

    WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE, WCECS 2015, VOL II   2220   835 - 840   2015

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:INT ASSOC ENGINEERS-IAENG  

    We study the problem of analyzing indoor location estimation by statistical radial distribution model. In this study, we suppose the observed distance data between transmitter and receiver as a statistical radial distribution. The proposed method is based on the marginal likelihoods of radial distribution generated by positive distribution among the several transmitter radio sites placed in the room. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the accuracy of location estimation of static case and dynamic case. In static experiment, subject is stationary state in some places in the chamber. This experiment is able to measure the precise performance of proposed method. In dynamic experiment, subject is move around in the chamber. This experiment is able to measure the suitability for practical use of proposed method. As a result, our method shows high accuracy for the indoor spatial location estimation compared to other previous methods..

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  • Statistical recognition of aspiration presence

    Shuhei Inui, Kosuke Okusa, Kurato Maeno, Toshinari Kamakura

    Lecture Notes in Electrical Engineering   247   541 - 553   2014

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Springer Verlag  

    A study on the healthcare application is very important for the solitary death in aging society. Many previous works had been proposed a detection method of aspiration using the non-contact radar. But the works are only in subjects with sitting in a chair. We consider that user falls down in the state when he happen abnormal situation as daily life. In this study, we focus on the detection of "aspiration" or "apnea" for the lying position, because the final decision of the life or death is aspiration. As initial stage of the system, we propose the recognition method for the presence of aspiration with lying position under the low-disturbance environment from microwave Doppler signals by using support vector machine (SVM). © 2014 Springer Science+Business Media Dordrecht.

    DOI: 10.1007/978-94-007-6818-5_38

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  • Human gait modeling and statistical registration for the frontal view gait data with application to the normal/abnormal gait analysis

    Kosuke Okusa, Toshinari Kamakura

    Lecture Notes in Electrical Engineering   247   525 - 539   2014

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:Springer Verlag  

    We study the problem of analyzing and classifying frontal view human gait data by registration and modeling on a video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameter. Our gait model is based on human gait structure and temporal-spatial relations between camera and subject. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the proposed method in gait analysis for young/elderly person and abnormal gait detecting. In abnormal gait detecting experiment, we apply K-NN classifier, using the estimated parameters, to perform normal/abnormal gait detect, and present results from an experiment involving 120 subjects (young person), and 60 subjects (elderly person). As a result, our method shows high detection rate. © 2014 Springer Science+Business Media Dordrecht.

    DOI: 10.1007/978-94-007-6818-5_37

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  • WEB PATH ANALYSIS FOR PURCHASE AND NON PURCHASE CUSTOMER

    Okusa Kosuke, Abe Kou, Inui Syuhei, Igarashi Yuuki, Iwai Yujiro, Kobayashi Chizuru, Tsujimura Tomoo, Fukumoto Keisuke, Lv Jiaxing, Yoshie Hayato, Kamakura Toshinari

    Bulletin of the Computational Statistics of Japan   27 ( 2 )   81 - 93   2014

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    Language:Japanese   Publisher:日本計算機統計学会  

    We study the problem of web site classification for purchase or non-purchase customer estimation. A study on data mining of web site access log data is very important role in the field of e-commerce and web site design. In this study, we focus on the customer's behavior in the e-commerce web site. Firstly, we detect the difference between purchase and non-purchase customer's behavior based on the graph model. Secondly, we reconstruct the web site classification based on the graph model's result. Finally, we estimate the purchase or non-purchase customer's behavior using HMM by the reconstructed web site classification. As a result, our classification method shows better performance than other method.

    DOI: 10.20551/jscswabun.27.2_81

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  • 個人の購買特性と閲覧回数を考慮した最適レコメンデーションシステムの設計(セッション5A スタディグループセッション「データカフェ」)

    森 健人, 秋元 良友, 加田 拓磨, 桑原 洋祐, 吉田 敦, 露崎 博之, 大草 孝介, 鎌倉 稔成

    日本計算機統計学会シンポジウム論文集   28   157 - 160   2014

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    DOI: 10.20551/jscssymo.28.0_157

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  • A study on gait parameter estimation stability for the frontal view gait video data based on simulation

    K. Okusa, T. Kamakura

    IAENG TRANSACTIONS ON ENGINEERING SCIENCES   421 - 428   2014

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:CRC PRESS-TAYLOR & FRANCIS GROUP  

    We study the problem of analyzing and classifying frontal view gait video data. The video data filmed from the frontal view is difficult to analyze, because the subject getting close in to the camera, and data includes the scale-changing parameters (Barnich and Droogenbroeck 2009, Lee et al. 2008). To cope with this, Okusa et al. (2011) and Okusa & Kamakura (2012) proposed a registration for scales of moving object using the method of nonlinear least squares, but Okusa et al. (2011) and Okusa & Kamakura (2012) did not focus on the human leg swing. Okusa & Kamakura (2013c) focus on the gait analysis using arm and leg swing model with estimated parameters and application to the normal/abnormal gait analysis. However, their models have many of parameters, and it raise calculation cost and instability of parameter estimation. Okusa & Kamakura (2013a) focus on the calculation cost and parameter estimation stability. The performance of Okusa & Kamakura (2013a) model is able to speed up the parameter estimation. However, the problem of parameter estimation stability still remains to be solved. Okusa & Kamakura (2013b) proposed simplified gait model based on the Okusa & Kamakura (2013a)'s model, it settled stability of parameter estimation. In this article, we focus on the behavior of Okusa & Kamakura (2013b) model's parameters. We validate the Okusa & Kamakura (2013b)'s model from the stand point of stability of the parameter estimation based on the numerical simulation. As a result, Okusa & Kamakura (2013b)'s gait model is stable to estimate the arm swim amplitude, subjects walking speed, gait frequency. However, on the other hand, this model is difficult to estimate the phase parameters. This result indicates Okusa & Kamakura (2013b) model is difficult to apply for the frontal view gait authentication.

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  • Fast gait parameter estimation for frontal view gait video data based on the model selection and parameter optimization approach

    Kosuke Okusa, Toshinari Kamakura

    IAENG International Journal of Applied Mathematics   43   220 - 225   2013.11

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    We study the problem of analyzing and classifying frontal view gait video data. In this study, we focus on the human walking speed and amplitude of arm swing and leg swing, we estimate these parameters using the statistical registration and modeling on a video data. To demonstrate the effectiveness of our method, we apply our gait parameter estimation model for the human gait video data. As a result, our model is able to estimate the gait parameters by stably at low calculation cost.

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  • Gait parameter and speed estimation from the frontal view gait video data based on the gait motion and spatial modeling

    Kosuke Okusa, Toshinari Kamakura

    IAENG International Journal of Applied Mathematics   43   37 - 44   2013.2

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    We study the problem of analyzing and classifying frontal view gait video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameters. We estimate these parameters using the statistical registration and modeling on a video data. Our gait model is based on human gait structure and temporal-spatial relations between camera and subject. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the proposed method in gait analysis for young/elderly person and abnormal gait detection. In abnormal gait detection experiment, we apply K-nearestneighbor classifier, using the estimated parameters, to perform normal/abnormal gait detect, and present results from an experiment involving 120 subjects (young person), and 60 subjects (elderly person). As a result, our method shows high detection rate.

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  • 検索条件の共起関係に基づく物件推薦アルゴリズムに関する統計的研究(スタディグループセッション「データカフェ」,セッション5A)

    大草 孝介, 阿部 興, 内藤 貴也, 山口 直人, 加田 拓磨, 黒田 淑恵, 佐藤 のぞみ, 日高 明日香, 森 健人, 鎌倉 稔成

    日本計算機統計学会大会論文集   27   129 - 132   2013

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    DOI: 10.20551/jscstaikai.27.0_129

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  • ドップラーセンサを用いた外乱環境下における生体検知に関する研究(セッション2A 一般セッション)

    大草 孝介, 鎌倉 稔成

    日本計算機統計学会シンポジウム論文集   27   41 - 44   2013

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    DOI: 10.20551/jscssymo.27.0_41

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  • Fast Frontal View Gait Authentication Based on the Statistical Registration and Human Gait Modeling

    Kosuke Okusa, Toshinari Kamakura

    WORLD CONGRESS ON ENGINEERING - WCE 2013, VOL I   1 LNECS   274 - 279   2013

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    Language:English   Publishing type:Research paper (international conference proceedings)   Publisher:INT ASSOC ENGINEERS-IAENG  

    We study the problem of analyzing and classifying frontal view gait video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameters. We estimate these parameters using the statistical registration and modeling on a video data. To demonstrate the effectiveness of our method, we conducted experiment, assessing the proposed method for frontal view human gait authentication. We apply K-nearest-neighbor classifier, using the estimated parameters, to perform the human gait authentication, and present results from an experiment involving 120 subjects. As a result, our method shows high recognition rate and low calculation cost.

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  • アクセス遷移の傾向に関する分析とそこから得られる知見について(スタディグループセッション「データカフェ」:平成23年度データ解析コンペティション報告)

    大草 孝介, 阿部 興, 乾 秀平, 五十嵐 悠貴, 岩井 佑二郎, 小林 千鶴, 辻村 朋大, 福元 啓祐, 呂 佳興, 吉江 勇人, 鎌倉 稔成

    日本計算機統計学会大会論文集   26   25 - 28   2012

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    DOI: 10.20551/jscstaikai.26.0_25

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  • A STATISTICAL REGISTRATION OF SCALE CHANGING AND MOVING OBJECTS WITH APPLICATION TO THE HUMAN GAIT ANALYSIS

    Okusa Kosuke, Kamakura Toshinari

    Bulletin of the Computational Statistics of Japan   24 ( 2 )   89 - 108   2012

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    We study the problems of the structure model and speed parameter estimation for scales of moving object on the video data with application to gait analysis. A study on the human gait is important in the fields of the biometrics study and the sports/health managements for planning optimal trainings. The motion capture system can give the precise measurements of trajectories of moving objects, but it requires the laboratory environments and this cannot be used in the field study. On the other hand, the video camera is handy to observe the gait motion in the field study, but such data has many restrictions on analysis based on the filming conditions. In particular, the video data filmed from the frontal-view is difficult to analyze, because the subject getting closer to the camera, and observed data includes the scale-changing parameters. To cope with this, Okusa et al. (2010) proposed a registration algorithm for scales of moving object using the method of nonlinear least squares with application to the gait analysis assuming constant speed. In this article, focusing on the human gait cycles and speeds, we consider the human gait modeling based on simple gait structure. We estimate the parameters of the human gait cycles and speeds using the method of nonlinear least squares (Okusa et al., 2010). We also show that estimated parameters may be used for the human gait analysis.

    DOI: 10.20551/jscswabun.24.2_89

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  • モーションキャプチャを用いた長距離走選手の運動フォームのモデリングに関する統計的研究(Session 4A(スポーツ統計))

    大草 孝介, 鎌倉 稔成

    日本計算機統計学会シンポジウム論文集   26   35 - 38   2012

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    DOI: 10.20551/jscssymo.26.0_35

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  • 移動体の大きさに関するレジストレーションと動作パラメータ・移動速度変動の推定 : 歩容解析への応用(セッション3B)

    大草 孝介, 鎌倉 稔成

    日本計算機統計学会大会論文集   25   121 - 124   2011

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    DOI: 10.20551/jscstaikai.25.0_121

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  • A STATISTICAL REGISTRATION OF SCALES OF MOVING OBJECTS WITH APPLICATION TO WALKING DATA

    Okusa Kosuke, Kamakura Toshinari, Murakami Hidetoshi

    Bulletin of the Computational Statistics of Japan   23 ( 2 )   97 - 111   2011

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    Language:Japanese   Publisher:日本計算機統計学会  

    A study on the motion picture plays an important role in the fields of authentication technology and sports managements for planning optimal trainings. However, such works depend on filming situation, and its difficult to analyze frontal view of scale-changing objects. The standard motion analysis software like "Dartfish" cannot handle the objects approaching to the camera. In this case, such software only shows series of picture image and it is hard to get numerical information from them. In this article we propose a statistical methodology that manage to extract information from the scale-changing objects based on the movie data by a consumer video camera and also apply this to real walking data.

    DOI: 10.20551/jscswabun.23.2_97

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  • ST-2 動画像に基づく歩行運動の特徴量の統計的比較(学生セッション)

    大草 孝介, 鎌倉 稔成, 村上 秀俊

    日本計算機統計学会大会論文集   22   109 - 112   2008

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    DOI: 10.20551/jscstaikai.22.0_109

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  • 歩行状態の動画データによる統計解析

    大草 孝介, 鎌倉 稔成

    日本計算機統計学会大会論文集   21   137 - 140   2007

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    Language:Japanese   Publisher:日本計算機統計学会  

    DOI: 10.20551/jscstaikai.21.0_137

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MISC

  • Human gait modeling and statistical registration for the frontal view gait data with application to the normal/abnormal gait analysis

    Kosuke Okusa, Toshinari Kamakura

    Lecture Notes in Electrical Engineering   247   525 - 539   2014

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    Language:English   Publisher:Springer Verlag  

    We study the problem of analyzing and classifying frontal view human gait data by registration and modeling on a video data. In this study, we suppose that frontal view gait data as a mixing of scale changing, human movements and speed changing parameter. Our gait model is based on human gait structure and temporal-spatial relations between camera and subject. To demonstrate the effectiveness of our method, we conducted two sets of experiments, assessing the proposed method in gait analysis for young/elderly person and abnormal gait detecting. In abnormal gait detecting experiment, we apply K-NN classifier, using the estimated parameters, to perform normal/abnormal gait detect, and present results from an experiment involving 120 subjects (young person), and 60 subjects (elderly person). As a result, our method shows high detection rate. © 2014 Springer Science+Business Media Dordrecht.

    DOI: 10.1007/978-94-007-6818-5_37

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  • Statistical Recognition of Aspiration Presence with Microwave Doppler Signals Reviewed

    Inui, S, Okusa, K, Maeno, K, Kamakura, T

    IAENG Transaction of Engineering Technologies   2013.8

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  • Gait Parameter and Speed Estimation from the Frontal View Gait Video Data Based on the Gait Motion and Spatial Modeling.

    Okusa, K, Kamakura, T

    International Journal of Applied Mathematics   43 ( 1 )   37 - 44   2013.1

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  • Normal/Abnormal Gait Analysis based on the Statistical Registration and Modeling of the Frontal View Gait Data. Reviewed

    Okusa, K, Kamakura, T

    Proceedings of WCECS2012   2012.10

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  • Statistical Estimation of the Accurate Location Based on the Indoor Positioning Systems.

    Okusa, K, Kamakura, T

    Proceedings of COMPSTAT2012   2012.8

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  • Statistical Registration and Modeling of Frontal View Gait Data with Application to the Human Recognition. Reviewed

    Okusa, K, Kamakura, T

    Proceedings of COMPSTAT2012   677 - 688   2012.8

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  • Statistical Disturbance Rejection of the Background Noise by Microwave Doppler Radar - Modelization of an Electric Fan Noise

    Tomoo Tsujimura, Kosuke Okusa, Kurato Maeno, Toshinari Kamakura

    WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE, WCECS 2012, VOL I   455 - 458   2012

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    Recently, the study with microwave Doppler radar is paid attention to. Microwave Doppler radar is one of the non-contact sensor, and detects the action of objects. The study focused on indoor human behavior has been developed. However, disturbance environment that pet and electronic device are moving in the room is considered in real daily life. We considered that an oscillating electric fan is most difficult disturbance environment to discriminate from human breathing, because the frequency range of which each signature appears is similar. In this paper, we propose a method to simulate the moving of an oscillating electric fan based on the data obtained from microwave Doppler radar. Finally, we evaluate the modelization of the moving of an oscillating electric fan. We compare computer simulation with metering experiment by residual sum of squares. As a result, our model shows good performance.

    Web of Science

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  • A STATISTICAL REGISTRATION OF SCALE CHANGING AND MOVING OBJECTS WITH APPLICATION TO THE HUMAN GAIT ANALYSIS

    Okusa Kosuke, Kamakura Toshinari

    Bulletin of the Computational Statistics of Japan   24 ( 2 )   89 - 108   2012

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    Language:Japanese   Publisher:Japanese Society of Computational Statistics  

    We study the problems of the structure model and speed parameter estimation for scales of moving object on the video data with application to gait analysis. A study on the human gait is important in the fields of the biometrics study and the sports/health managements for planning optimal trainings. The motion capture system can give the precise measurements of trajectories of moving objects, but it requires the laboratory environments and this cannot be used in the field study. On the other hand, the video camera is handy to observe the gait motion in the field study, but such data has many restrictions on analysis based on the filming conditions. In particular, the video data filmed from the frontal-view is difficult to analyze, because the subject getting closer to the camera, and observed data includes the scale-changing parameters. To cope with this, Okusa et al. (2010) proposed a registration algorithm for scales of moving object using the method of nonlinear least squares with application to the gait analysis assuming constant speed. In this article, focusing on the human gait cycles and speeds, we consider the human gait modeling based on simple gait structure. We estimate the parameters of the human gait cycles and speeds using the method of nonlinear least squares (Okusa et al., 2010). We also show that estimated parameters may be used for the human gait analysis.

    DOI: 10.20551/jscswabun.24.2_89

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  • Recognizing Aspiration Presence using Model Parameter Classification from Microwave Doppler Signals

    Shuhei Inui, Kosuke Okusa, Kurato Maeno, Toshinari Kanakura

    WORLD CONGRESS ON ENGINEERING AND COMPUTER SCIENCE, WCECS 2012, VOL I   509 - 512   2012

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    A study on the healthcare application is very important for the solitary death in aging society. Many previous works had been proposed a detection method of aspiration using the non -contact radar. But the works are only in subjects with sitting in a chair. We consider that user falls down in the state when he happen abnormal situation as daily life.
    In this study, we focus on the detection of "aspiration" or "apnea" for the lying position, because the final decision of the life or death is aspiration. As initial stage of the system, we propose the recognition method for the presence of aspiration with lying position under the low-disturbance environment from microwave Doppler signals by using support vector machine (SVM).

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  • Statistical Heartbeat Pace Estimation Based on the Microwave Doppler Sensor Data

    Inui, S, Okusa, K, Kamakura, T

    Proc. Joint Meet. Kor.-Jpn. Conf. Comput. Statist. & Symp. Jpn. Soc. Comput. Statist   25   61 - 64   2011.11

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  • Statistical Gait Analysis Based on the Microwave Doppler Sensor Data

    Fukumoto, K, Okusa, K, Kamakura, T

    Proc. Joint Meet. Kor.-Jpn. Conf. Comput. Statist. & Symp. Jpn. Soc. Comput. Statist   25   57 - 60   2011.11

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  • Feature Selection for Conditional Random Field Based on the Multivariate Time Series Data with Application to the Activity Recognition

    Tsujimura, T, Okusa, K, Kamakura, T

    Proc. Joint Meet. Kor.-Jpn. Conf. Comput. Statist. & Symp. Jpn. Soc. Comput. Statist   25   107 - 110   2011.11

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  • A Statistical Registration of Scale-Changing and Moving Objects with Application to the Human Gait Authentication

    Okusa, K, Kamakura, T

    ISI World Statist. Cong. 2011 (ISI2011)   CPS017 - 01   2011.8

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  • An application of the sound recognition technique to the human action acknowledgment

    Uemizo, I, Okusa, K, Kamakura, T

    Australian Statistical Conference 2010 (ASC 2010)   p.239   2010.12

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  • Statistical classification algorithm for infrasonic frequency multivariate time-series data with application to human activity recognition

    Okusa, K, Kamakura, T

    Australian Statistical Conference 2010 (ASC 2010)   p.184   2010.12

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  • 動画像に基づく移動オブジェクトの大きさに関する統計的レジストレーション - 歩行動画像への応用 Reviewed

    大草孝介, 鎌倉稔成, 村上秀俊

    計算機統計学   23 ( 2 )   97 - 111   2010

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    Language:Japanese   Publisher:日本計算機統計学会  

    A study on the motion picture plays an important role in the fields of authentication technology and sports managements for planning optimal trainings. However, such works depend on filming situation, and its difficult to analyze frontal view of scale-changing objects. The standard motion analysis software like "Dartfish" cannot handle the objects approaching to the camera. In this case, such software only shows series of picture image and it is hard to get numerical information from them. In this article we propose a statistical methodology that manage to extract information from the scale-changing objects based on the movie data by a consumer video camera and also apply this to real walking data.

    DOI: 10.20551/jscswabun.23.2_97

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  • Statistical Gait Analysis by Extraction of Walking Features from the Movie Data

    ( 39 )   2009.7

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Presentations

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Works

  • 電波センサの時系列信号処理によるリアルタイム状況推定技術の開発

    2011.10 -  

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Awards

  • 学術研究奨励賞

    2013.3   中央大学  

  • データ解析コンペティション課題設定部門 日本計算機統計学会スタディグループ 優秀賞

    2013.2   日本計算機統計学会  

  • Certificate of Merit

    2012.11   International Association of Engineers   Normal/Abnormal Gait Analysis based on the Statistical Registration and Modeling of the Frontal View Gait Data.

  • 奨励賞

    2012.5   日本計算機統計学会   動画像に基づく移動オブジェクトの大きさに関する統計的レジストレーション - 歩行動画像への応用 及び 移動体の大きさの変動を考慮した歩容解析のための動作パラメータ・移動速度変動の推定

  • データ解析コンペティション自由課題学生部門 日本計算機統計学会スタディグループ 優秀賞

    2012.3   日本計算機統計学会  

  • 渋谷健一賞

    2011.3   中央大学   多次元時系列データのクラス分類に関する研究‐行動認識への応用

  • 優秀ポスター発表賞

    2010.5   応用統計学会   多次元時系列データのクラス分類に関する研究‐行動認識への応用

  • 学員会会長賞

    2009.3   中央大学   動画像に基づく歩行運動の特徴量の統計的比較

  • 学生研究発表賞

    2008.5   日本計算機統計学会   動画像に基づく歩行運動の特徴量の統計的比較

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Research Projects

  • Development of pattern recognition algorithm for ultra low frequency multivariate time-series data considering dimensional correlation

    Grant number:21K11938  2021.4 - 2024.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (C)  Yokohama City University

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    Grant amount: \3770000 ( Direct Cost: \2900000 、 Indirect Cost: \870000 )

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  • Service Design Utilizing Daily Life Information to Improve the Quality of Life of the Healthy Older People

    Grant number:15H01761  2015.4 - 2018.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research (A)  Kyushu University

    Tamura Ryoichi

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    Grant amount: \38610000 ( Direct Cost: \29700000 、 Indirect Cost: \8910000 )

    This study aims to consider services utilizing daily life information to improve the quality of life of healthy older people through conducting the large-scale questionnaire survey, the field survey using devices to measure indoor or outdoor daily life, and consideration of the indoor sensing technology.
    As a result, from the questionnaire survey, it was found that proposal of services aiming for enjoyment, anxiety, and ikigai are necessary considering the differences in household structure and gender. From field survey, we found the possibility of development of applications utilizing living records, and humane services that watch based on daily life information. And we built the indoor position estimation algorithm using RSS type sensors.

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  • A study on pattern recognition of infrasonic multivariate time-series data

    Grant number:26730021  2014.4 - 2017.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Young Scientists (B)  Kyushu University

    OKUSA KOSUKE

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    Grant amount: \2990000 ( Direct Cost: \2300000 、 Indirect Cost: \690000 )

    In this research, we focused on statistical analysis of multivariate low frequency stream data, especially the pattern recognition method. To confirm the performance of proposed method, we mainly focused on the sensing data analysis which is a typical example of multivariate low frequency stream data.
    In this study, as a specific example, we focused on two cases of sensing data analysis. First case is developing the life-watching system using microwave Doppler rader. Second case is statistical indoor location estimation system using ToA/RSS measurement system. Finally, our proposed method showed good performance for both examples than previous methods.
    These results were reported to peer-reviewed papers and international conferences.

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  • Evaluation of location estimates based on the Radial distributions generated by positive distributions

    Grant number:26540014  2014.4 - 2017.3

    Japan Society for the Promotion of Science  Grants-in-Aid for Scientific Research  Grant-in-Aid for Challenging Exploratory Research  Chuo University

    Kamakura Toshinari, OKUSA Kosuke

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    Grant amount: \3640000 ( Direct Cost: \2800000 、 Indirect Cost: \840000 )

    We have developed algorithms for finding the confidence region for specifying the confidence level that trusts the location estimates by constructing the statistical model and estimating its parameters of the position estimation of the person in the room with high precision. It is possible to accurately estimate the location parameter by the rotation distributions from the Weibull distribution and the lognormal distribution which are positive distributions. By using the implicit function theorem, we can calculate the asymptotic distribution of the conditional maximum likelihood estimators for confidence regions of the location.

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  • 電波センサの時系列信号処理によるリアルタイム状況推定技術の開発

    2011.10 -  

    JST科学技術振興機構・研究成果最適展開支援プログラム 

    鎌倉稔成

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    Grant type:Competitive

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