Publication
Journal Papers
[1] Y. Miyagi, M. Onishi, C. Watanabe, T. Itoh, M. Takatsuka, Classification and Visualization for Symbolic People Flow Data, Journal of Visual Languages and Computing, Vol. 43, pp. 91-102, December 2017.
[2] 宮城, 大西, 渡辺, 伊藤, 高塚, 記号化された歩行経路群のパターン抽出と可視化, 可視化情報学会論文集, Vol. 38, No. 3, pp. 7-16, 2018 年 3 月.
[3] 宮城, Rodrigues, Weiskopf, 伊藤, N-gram による視線軌跡からのAOI 推移パターン抽出と軌跡形状の可視化, 芸術科学会論文誌, Vol. 18, No. 4, pp. 125-133, 2019 年 11 月 (NICOGRAPH2019 最優秀論文賞).
Conference Talks in English
[4] Y. Miyagi, M. Onishi, C. Watanabe, T. Itoh, M. Takatsuka: Feature Extraction and Visualization for Symbolic People Flow Data, IEEE Pacific Visualization Symposium, Poster Session, April 2016.
[5] Y. Miyagi, M. Onishi, C. Watanabe, T. Itoh, M. Takatsuka: Feature Extraction and Visualization for Symbolic People Flow Data, 20th International Conference on Information Visualisation (IV2016), July 2016 (The Best Paper Award).
[6] Y. Miyagi, M. Onishi, C. Watanabe, T. Itoh, M. Takatsuka: Classification and Visualization for Symbolic People Flow Data Preserving Way Points and Staying Times, IEEE Pacific Visualization Symposium, Poster Session, April 2017.
[7] Y. Miyagi, N. Rodrigues, D. Weiskopf, T. Itoh: Visualization of Eye Tracking Data Using a Directed Graph with Edge Bundling, IEEE Pacific Visualization Symposium, Poster Session, April 2018.
[8] Y. Miyagi, N. Rodrigues, D. Weiskopf, T. Itoh: Analysis and Graph Visualization of Eye Tracking Data with a Static Stimulus, IEEE VIS, Poster Session, October 2018.
[9] Y. Miyagi, N. Rodrigues, D. Weiskopf, T. Itoh: Pattern Extraction and Visualization of Eye Tracking Scan Paths on Hierarchical AOIs, IEEE Pacific Visualization Symposium, Poster Session, April 2019.
Conference Talks in Japanese
[10] 宮城, UniversalSAX を用いた人流可視化, 第 14 回 ビジュアル情報処理研究合宿, 2014 年 9 月.
[11] 宮城, 大西, 渡辺, 伊藤UniversalSAX を用いた人流可視化, 第 5 回情報可視化研究合宿, 2014 年 9 月.
[12] 宮城, 大西, 渡辺, 伊藤, 文字列化による人流データの圧縮と可視化, 第 7 回データ工学と情報マネジメントに関するフォーラム(DEIM 2015), F8-5, 2015 年 3 月 (学生プレゼンテーション賞).
[13] 宮城, 大西, 渡辺, 伊藤, UniversalSAX を用いた人流可視化, 情報処理学会第 77 回全国大会, 4N-08, 2015 年 3 月 (学生奨励賞, 大会奨励賞).
[14] 宮城, 大西, 渡辺, 伊藤, 記号化による人流データの圧縮と可視化, 第 18 回画像の認識・理解シンポジウム, SS5-9, 2015 年 7 月.
[15] 宮城, 大西, 渡辺, 伊藤記号化による人流データの圧縮と可視化, 第 15 回 ビジュアル情報処理研究合宿, 2015 年 9 月.
[16] 宮城, 大西, 渡辺, 伊藤, 高塚記号化による人流データの圧縮と可視化, 第 6 回情報可視化研究合宿, 2015 年 9 月.
[17] 宮城, 大西, 渡辺, 高塚, 伊藤, 記号列化した人流データからの特徴抽出と可視化, 第 8 回データ工学と情報マネジメントに関するフォーラム(DEIM 2016), F3-5, 2016年 3 月 (学生プレゼンテーション賞).
[18] 宮城, 大西, 渡辺, 伊藤, 高塚, 記号列化した人流データからの特徴抽出と可視化, 情報処理学会第 78 回全国大会, 4N-05, 2016 年 3 月 (学生奨励賞, 大会優秀賞).
[19] 宮城, 大西, 渡辺, 伊藤, 高塚記号化された歩行経路群のパターン抽出と可視化, 第 7 回情報可視化研究合宿, 2016 年 9 月.
[20] 宮城, 大西, 渡辺, 伊藤, 高塚, 通過点と滞在時間情報を保持し記号列化した歩行者動線の分類と可視化, 情報処理学会第 79 回全国大会, 4P-02, 2017 年 3 月.
[21] 宮城, 大西, 渡辺, 伊藤, 高塚, 通過点と滞在時間情報を保持し記号列化した歩行者動線の分類と可視化, 第 45 回可視化情報シンポジウム, B205, 2017 年 7 月.
[22] 宮城, 大西, 渡辺, 伊藤, 高塚通過点と滞在時間情報を保持し記号列化した歩行者動線の分類と可視化, 第 8 回情報可視化研究合宿, 2017 年 9 月.
[23] 宮城, 大西, 渡辺, 伊藤, 高塚, 室内で撮影した歩行者軌跡を対象としたパターン分析と可視化, 第 1 回ビジュアリゼーションワークショップ, ポスターセッション, 2018年 3 月.
[24] 宮城, 大西, 渡辺, 伊藤, 高塚, RGB-D カメラで記録した歩行者軌跡のパター ン分析と可視化, 第 46 回可視化情報シンポジウム, 2018 年 7 月 (ベストプレゼンテーション賞).
[25] 宮城, Weiskopf, 伊藤, 階層的なAOI を用いた視線軌跡のパターン分析と可視化, 第 2 回ビジュアリゼーションワークショップ, ポスターセッション, 2019 年 3 月.
[26] 宮城, Rodrigues, Weiskopf, 伊藤, 力指向グラフによる視線推移パターンの可視化と比較, 第 47 回可視化情報シンポジウム, 2019 年 7 月.
[27] 宮城, Rodrigues, Weiskopf, 伊藤N-gram による視線軌跡からのAOI 推移パターン抽出と形状可視化, 第 10 回情報可視化研究合宿, 2019 年 9 月.
Bibliography
[28] Y. Zheng, Trajectory Data Mining: An Overview, ACM Transactions on Intelligent Systems and Technology, 6(3), 41, 2015.
[29] 気 象 庁, 台 風 情 報 の 種 類 と 表 現 方 法, https://www.jma.go.jp/jma/kishou/know/typhoon/7-1.html
[30] N. Andrienko, G. Andrienko, Visual analytics of movement: An overview of methods, tools and procedures, Information Visualization, 12(1), 3-24, 2013.
[31] T. Yamashita, S. Soeda, M. Onishi, I. Yoda, I. Noda, Approach to Safety and Secure Evacuation with Sensor Data Mining, The journal of the Institute of Electronics, Information and Communication Engineerss, 94(4), 294-298, 2011.
[32] A. Li, Z. Chen, Representative Scanpath Identification for Group Viewing Pattern Analysis, Journal of Eye Movement Research, 11(6), 179-194, 2018.
[33] S. Konomi, H. Ishizuka, M. Iwai, J. Miyazaki, K. Sezaki, Y. Tobe, I-Tree: A Spatial Time-series Indexing Mechanism for Supporting Integrated Retrieval of Sensing Data, IPSJ Transactions on Databases, 4(1), 26-39, 2011.
[34] T. Oates, A. P. Boedihardjo, J. Lin, C. Chen, S. Frankenstein, S. Gandhi, Motif Discovery in Spatial Trajectories using Grammar Inference, ACM International Conference on Information and Knowledge Management (CIKM 2013), 1465-1468, 2013.
[35] Y. Ohata, A. Ohno, T. Yamasaki, K. Tokiwa, An analysis of shopping behavior pattern and purchase amount in the inner areas of the sales floor in a retail store, Proceedings of the Forum on Information Technology 2015, 14(2) 297-302, 2015.
[36] K. Yada, String analysis technique for shopping path in a supermarket. Journal of Intelligent Information Systems, 36(3), 385-402, 2011.
[37] K. Teknomo, G. P. Gerilla, Pedestrian Static Trajectory Analysis of a Hypermarket, Proceedings of the Eastern Asia Society for Transportation Studies, 7, 2009.
[38] M. Burch, A. Kumar, K. Mueller, The Hierarchical Flow of Eye Movements, Proceedings of the 3rd Workshop on Eye Tracking and Visualization, 1-5, 2018.
[39] C. K. Yang, C. Wacharamanotham Alpscarf: Augmenting Scarf Plots for Exploring Temporal Gaze Patterns, Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, 1-6, 2018.
[40] N. Johnson, D. Hogg, Learning the Distribution of Object Trajectories for Event Recognition, Image and Vision Computing, 14(8), 609-615, 1996.
[41] F. Porikli, T. Haga, Event Detection by Eigenvector Decomposition Using Object and Frame Features, Computer Vision and Pattern Recognition Workshop, 114- 114, 2004.
[42] N. Suzuki, K. Hirasawa, K. Tanaka, T. Kobayashi, Y. Sato, Y. Fujino, Detection of Abnormal Behavior and Patterns by Human Trajectories Analysis, The IEICE transactions on information and systems (Japanese edition), 91(6), 1550-1560, 2008.
[43] A. Asahara, A. Sato, K. Maruyama, Indoor and Outdoor Pedestrian Trajectory Analysis and the Experiment, IPSJ SIG technical reports, 135, V1-V8, 2009.
[44] M. Butenuth, F. Burkert, F. Schmidt, S. Hinz, D. Hartmann, A. Kneidl, A. Borrmann, B. Sirmacek, Integrating pedestrian simulation, tracking and event detection for crowd analysis , 2011 IEEE International Conference on Computer Vision Workshops, 150-157, 2011.
[45] G. Andrienko, N. Andrienko, S. Wrobel, Visual Analytics Tools for Analysis of Movement Data, ACM SIGKDD Explorations Newsletter, 9(2), 38-46, 2007.
[46] H. Yabushita, T. Itoh, Summarization and Visualization of Pedestrian Tracking Data, 15th International Conference on Information Visualisation (IV2011), 537- 542, 2011.
[47] A. Fukute, M. Onishi, T. Itoh, A Linked Visualization of Trajectory and Flow Quantity to Support Analysis of People Flow, 17th International Conference on Information Visualisation (IV2013), 561-567, 2013.
[48] H. Guo, Z. Wang, B. Yu, H. Zhao, X. Yuan, TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection, IEEE Pacific Visualization Symposium, 163-170, 2011.
[49] Z. Wang, H. Guo, X. Yuan, H. Liu, H. Zhang, Discovery Exhibition: Visual Analysis on Traffic Trajectory Data, Poster Proceedings of IEEE Visualization Discovery Exhibition, 2011.
[50] Y. Guo, Q. Xu, X. Li, X. Luo, M. Sbert, A New Scheme for Trajectory Visualization, 18th International Conference on Information Visualisation (IV2014), 40-45, 2014.
[51] Z. Wang, T. Ye, M. Lu, X. Yuan, H. Qu, J. Yuan, Q. Wu, Visual Exploration of Sparse Traffic Trajectory Data, IEEE Transactions on Visualization and Computer Graphics, 20(12), 1813-1822, 2014.
[52] S. Al-Dohuki, F. Kamw, Y. Zhao, C. Ma, Y. Wu, J. Yang, X. Ye, F. Wang, X. Li, W. Chen, SemanticTraj: A New Approach to Interacting with Massive Taxi Trajectories. IEEE Transactions On Visualization and Computer Graphics, 23(1), 11-20, 2017.
[53] R. Krueger, D. Thom, M. Woerner, H. Bosch, and T. Ertl, TrajectoryLenses- A Set-based Filtering and Exploration Technique for Long-term Trajectory Data, Computer Graphics Forum (proceedings of The Eurographics Conference on Visualization), 32 (3), 451-460, 2013.
[54] R. Krueger, S. Koch, T. Ertl, Saccadelenses: interactive exploratory filtering of eye tracking trajectories, 2016 IEEE Second Workshop on Eye Tracking and Visualization, 31-34, 2016.
[55] T. Kuebler W. Fuhl, R. Rosenberg, E. Kasneci, Novel Methods for Analysis and Visualization of Saccade Trajectories, Computer Vision – ECCV 2016 Workshops, 783-797, 2016.
[56] M. Ramin, A Streakline Representation of Flow in Crowded Scenes, Computer Vision – ECCV 2010, 439-452, 2010.
[57] N. Rodrigues, R. Netzel, J. Spalink, D. Weiskopf, Multiscale scanpath visualization and filtering, Proceedings of the 3rd Workshop on Eye Tracking and Visualization, 1-5, 2018.
[58] D. Rudi, P. Kiefer, M. Raubal Visualizing pilot eye movements for flight instructors, Proceedings of the 3rd Workshop on Eye Tracking and Visualization, 1-5, 2018
[59] S. Okazaki, S. Matsushita, A study of simulation model for pedestrian movement with evacuation and queuing, International Conference on Engineering for Crowd Safety, 271, 1993.
[60] L. Chittaro, L. Ieronutti, A Visual Tool for Tracing Users ’ Behavior in Virtual Environments, Proceedings of the working conference on Advanced visual interfaces, 40-47, 2004.
[61] R. Krueger, G. Sun, F. Beck, R. Liang, T. Ertl, TravelDiff: Visual comparison analytics for massive movement patterns derived from Twitter, IEEE Pacific Visualization Symposium, 176-183, 2016.
[62] S. Gupta, M. Dumas, M. J. McGuffin,m T. Kapler, MovementSlicer: Better Gantt charts for visualizing behaviors and meetings in movement data, IEEE Pacific Visualization Symposium, 168-175, 2016.
[63] N. H. Thach, E. Suzuki, A Symbolic Representation for Trajectory Data, The Japanese Society Artificial Intelligence, 1A2-2, 2010.
[64] X. Alameda-Pineda, Y. Yan, E. Ricci, O. Lanx, N. Sebe, Analyzing Free-standing Conversational Groups: A Multimodal Approach, the 23rd ACM international conference, 5-14, 2015.
[65] C. M. Privitera, L. W. Stark, Algorithms for defining visual regions-of-interest: comparison with eye fixations, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(9), 970-982, 2000.
[66] P. Muthumanickam, K. Vrotsou, A. Nordman, J. Johansson, M. Cooper, Identification of Temporally Varying Areas of Interest in Long Duration Eye Tracking Data Sets, IEEE Transactions on Visualization and Computer Graphics, 25, 87-97, 2018.
[67] T. Blascheck, M. Schweizer , F. Beck, T. Ertl, Visual Comparison of Eye Movement Patterns, Comput. Graph. Forum, 36(3), 87-97, 2017.
[68] M. Burch, A. Kumar, K. Mueller, D. Weiskopf, Color bands: visualizing dynamic eye movement patterns, Proceedings of the 2nd Workshop on Eye Tracking and Visualization, 40-44, 2016.
[69] M. Burch, K. Kurzhals, N. Kleinhans, D. Weiskopf EyeMSA: Exploring Eye Movement Data with Pairwise and Multiple Sequence Alignment, Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications, 1-5, 2018.
[70] Y. Gu, C. Wang, R. Bixler, S. D ’Mello, ETGraph: A Graph-Based Approach for Visual Analytics of Eye-Tracking Data, Computers & Graphics, 62, 1–14, 2017.
[71] V. Peysakhovich, C. Hurter, Scanpath visualization and comparison using visual aggregation techniques, Journal of Eye Movement Research, 10(5), 1-14, 2018.
[72] M. Onishi T. Yamashita T. Hoshikawa, K. Sato, Transmission of Knowledge for Evacuation Drill using Pedestrian Tracking and Simulation - Example of Opera Concert with Evacuation Drill in New National Theatre, The Japanese Society for Artificial Intelligence Special Interest Group on Knowledge and Skills Transfer, SIG-KST-026-06, 2015.
[73] A. Onishi, C. Watanabe, Universal SAX: Applied SAX to the Multidimensional Time Series Data Using the Space Filling Curve, DBSJ Journal, 11(1), 43-48, 2012.
[74] M. Onishi, I. Yoda, Dynamic Trajectory Extraction from Stereo Vision Using Fuzzy Clustering, The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 128, 9, 1438-1446, 2008.
[75] H. Hikita, M. Onishi, A fault tolerant autonomous distributed system for pedestrian measurement using multiple cameras, CVIM, 2017-CVIM-205(26), 1-6, 2017.
[76] K. Yarimizu, “Weighted Levenshtein Distance” for Calculating the Distance between Words, Meikai Japanese language journal (18), 179-194, 2013.
[77] S. Eraslan, Y. Yesilada, S. Harper, Scanpath Trend Analysis on Web Pages: Clustering Eye Tracking Scanpaths, ACM Trans. Web, 10(4), 1-35, 2016.
[78] U. Obaidellah, M. Al Haek, P. C-H. Cheng, A Survey on the Usage of Eye-Tracking in Computer Programming, ACM Computing Surveys, 51(1), 58, 2018.
[79] T. Blascheck, K. Kurzhals, M. Raschke, M. Burch, D. Weiskopf, T. Ertl, Visualization of Eye Tracking Data: A Taxonomy and Survey, Computer Graphics Forum, 36(8), 260-284, 2017.
[80] T. Blascheck, K. Kurzhals, M. Raschke, M. Burch, D. Weiskopf, T. Ertl, State- of-the-Art of Visualization for Eye Tracking Data, Eurographics Conference on Visualization, 2014.
[81] K. Holmqvist, J. Holsanova, M. Barthelson, D. Lundqvist, Reading or scanning? A study of newspaper and net paper reading, The mind’s eye: cognitive and applied aspects of eye movement research, 657-670, 2003.
[82] K. Kurzhals, M. Burch, T. Blascheck, G. Andrienko, N. Andrienko, D. Weiskopf A task-based view on the visual analysis of eye-tracking data, Mathematics and Visualization, 3-22, 2017.
[83] C.E. Shannon, Prediction and entropy of printed English, Bell Syst. Tech. J., 30, 50-64, 1951.
[84] T. Blascheck, K. Kurzhals, M. Raschke, S. Strohmaier, D. Weiskopf, T. Ertl AOI hierarchies for visual exploration of fixation sequences, Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications, 111-118, 2016.
[85] D. Holten, J. J. van Wijk Force-directed edge bundling for graph visualization, Eurographics/ IEEE-VGTC Symposium on Visualization 2009, 983-998, 2009.
[86] M. Tennekes, E. de Jonge, Tree Colors: Color Schemes for Tree-Structured Data, Ieee Transactions on Visualization and Computer Graphics, 20(12) 2072-2081, 2014.
[87] M. Reani, N. Peek, C. Jay An Investigation of the Effects of N-gram Length in Scanpath Analysis for Eye-tracking Research, Proceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications, 1-8, 2018.