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  1. NTU Theses and Dissertations Repository
  2. 管理學院
  3. 資訊管理學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/28929
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dc.contributor.advisor莊裕澤(Yuh-Jzer Joung)
dc.contributor.authorKuan-Wei Pengen
dc.contributor.author彭冠瑋zh_TW
dc.date.accessioned2021-06-13T00:30:05Z-
dc.date.available2011-08-18
dc.date.copyright2011-08-18
dc.date.issued2011
dc.date.submitted2011-08-04
dc.identifier.citationReferences
[1] Marion Alexander and Adrian Honish. “Table Tennis: A Brief Overview of Biomechanical Aspects of the Game for Coaches and Players,” Sport Biomechanics Laboratory Faculty of Kinesiology and Recreation Management University of Manitoba, 2009.
[2] Card, S.K., Mackinlay, J.D., and Shneiderman, B., Readings in Information Visualization - Using Vision to Think, San Francisco, CA: Morgan Kaufmann Publishers, 1999.
[3] Keim, D.A., “Information Visualization and Visual Data Mining”, IEEE Transactions on Visualization and Computer Graphics, Vol. 8, No. 1, January-March 2002.
[4] DECAMP P., FRID-JIMENEZ A., GUINESS J., ROYD. : Gist icons: Seeing meaning in large bodies of literature. In Proc. of IEEE Symp. on Information Visualization, Poster Session (Oct. 2005).
[5] Weber W. Text Visualization-What Colors Tell About a Text. In Proceedings of the IEEE 11th International Conference on Information Visualization (IV ’07), pages 354–362, 2007.
[6] D. A. Keim, J. Schneidewind, and M. Sips. Circleview: a new approach for visualizing time-related multidimensional data sets. In Proc. of Advanced Visual Interfaces, pages 179–182. ACM Press, 2004.
[7] Kumar, N., Lolla N., Keogh, E., Lonardi, S., Ratanamahatana, C., & Li, W. (2005). Time-series Bitmaps: A Practical Visualization Tool for working with Large Time Series Databases. SIAM Data Mining Conference.
[8] Pingali, G. et al., Visualization of sports using motion trajectories: providing insights into performance, style, and strategy, In the Procs. Conference on visualization, 2001.
[9] Jin, L. and Banks, D. C. Visualizing a tennis match. Proceedings of the IEEE Symposium on Information Visualization (INFOVIS '96), IEEE Computer Society, 1996.
[10] B. Shneiderman, “The eye have it: A task by data type taxonomy for information visualizations,” in Visual Languages, 1996.
[11] L. Nowell S. Havre, B. Hetzler and P. Whitney, “Themeriver: Visualizing thematic changes in large document collections,” Transactions on Visualization and Computer Graphics, 2001.
[12] D. Tang C. Stolte and P. Hanrahan, “Polaris: A system for query, analysis and visualization of multi-dimensional relational databases,” Transactions on Visualization and Computer Graphics, 2001.
[13] J. Abello and J. Korn, “Mgv: A system for visualizing massive multi-digraphs,” Transactions on Visualization and Computer Graphics, 2001.
[14] N. Lopez, M. Kreuseler and H. Schumann, “A scalable framework for information visualization,” Transactions on Visualization and Computer Graphics, 2001.
[15] D. Keim, “Designing pixel-oriented visualization techniques: Theory and applications,” Transactions on Visualization and Computer Graphics, vol. 6, no. 1, pp. 59–78, Jan–Mar 2000.
[16] B. Shneiderman, “Tree visualization with treemaps: A 2D space-filling approach,” ACM Transactions on Graphics, vol. 11, no.1, pp. 92–99, 1992.
[17] B. Johnson and B. Shneiderman, “Treemaps: A space-filling approach to the visualization of hierarchical information,” in Proc. Visualization ’91 Conf, 1991, pp. 284–291.
[18] M. O. Ward, “Xmdvtool: Integrating multiple methods for visualizing multivariate data,” in Proc. Visualization 94, Washington, DC, 1994, pp. 326–336.
[19] D. Asimov, “The grand tour: A tool for viewing multidimensional data,” SIAM Journal of Science & Stat. Comp., vol. 6, pp. 128–143, 1985.
[20] Goh, K. I. et al. The human disease network. Proc. Natl Acad. Sci. USA 104, 8685–8690 (2007).
[21] OELKE D., BAK P., KEIM D. A., LAST M., DANONG.: Visual evaluation of text features for document summarization and analysis. In Proc. of the IEEE Symp. on Visual Analytics Science and Technology (VAST) (2008), pp. 75–82.
[22] HEARST M. A.: Tilebars: visualization of term distribution information in full text information access. In Proc. of the SIGCHI Conf. on Human Factors in Computing Systems (1995), ACM Press, pp. 59–66.
[23] D. A. Keim and D. Oelke. Literature fingerprinting: A new method for visual literary analysis. In EEE Symposium on Visual Analytics and Technology (VAST 2007), pages 115–122, 2007.
[24] WATTENBERG M., VIEGAS F. B.: The word tree, and interactive visual concordance. IEEE Transactions on Visualization and Computer Graphics (Proc. of the IEEE Conf. on Information Visualization) 14, 6 (Nov/Dec 2008), 1221–1229.
[25] C. Collins, S. Carpendale, G. Penn, Docuburst: visualizing document content using language structure, in: Proceedings of Eurographics/IEEE-VGTC Symposium on Visualization (EuroVis ’09), Eurographics Association, 2009, pp. 1039–1046.
[26] Grinstein, G., Trutschl, M. and Cvek, U.: High-Dimensional Visualizations, in Workshop on Visual Data Mining, ed. by Keim, A. and Eick, St., San Francisco, KDD - 2001.
[27] D. A. Keim, T. Nietzschmann, N. Schelwies, J. Schneidewind, T. Schreck, and H. Ziegler. A spectral visualization system for analyzing financial time series data. In EuroVis 2006: Eurographics/IEEE-VGTC Symposium on Visualization, Lisbon, Portugal, 8-10 May, 2006.
[28] Virtual Spectator. Cricket Super Score. URL: http://www.pineapplehead.com.au/. Accessed 5 Oct 2005.
[29] ESPN URL: http://sports.espn.go.com/nba. Accessed 5 Oct 2005.
[30] E.Tufte. Beautiful Evidence. Cheshire, CT, Graphics Press. 2006.
[31] Yu, L. J., Zhang, H. & Hu, J. J. Computer diagnostics for the analysis of table tennis matches. International Journal of Sports Science and Engineering, 2, 144-153, 2008.
[32] H. Zhang and A. Hohmann. Performance Diagnosis through Mathematical Simulation in Table tennis Game. Journal of Shanghai University of Sport. 2004, 28(2): 68-72.
[33] H. Zhang. Diagnosis and Analysis through computer in the ball game. HeiLongJiang Science And Technology Press, 2006, pp.50-73.
[34] Telea A., de Hillerin P., Văleanu V., Visualization of Multivariate Athlete Performance Data, Proceedings of the Seventh IASTED International Conference on Visualization, Imaging, and Image Processing, Publication Code: 583, 2007 ACTA Press, August 29 – 31, 2007.
[35] L. Yu, H. Zhang, J. Dai, et al. Theory and Methods of Analyzing Techniques & Tactics of Net Antagonistic Event Competitions. Journal of Shanghai University of Sport. 2007, 31(3): 48-53.
[36] Whigham, Peter A, Keep your eye on the ball: Local versus global statistics in sport visualization, 2005.
[37] D. Nadalutti and L. Chittaro, Visual analysis of users’ performance data in fitness activities, Comput. Graph. 31 (3) (2007), pp. 429–439.
[38] Yingcai Wu; Furu Wei; Shixia Liu; Au, N.; Weiwei Cui; Hong Zhou; Huamin Qu; , 'OpinionSeer: Interactive Visualization of Hotel Customer Feedback,' Visualization and Computer Graphics, IEEE Transactions on , vol.16, no.6, pp.1109-1118, Nov.-Dec. 2010
[39] Information Visualization Evaluation – WikiViz. http://www.wikiviz.org/wiki/Information_Visualization_Evaluation
[40] Plaisant, C. The challenge of information visualization evaluation. Proceedings of the working conference on Advanced visual interfaces (AVI04). pp. 109 – 116. 2004.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/28929-
dc.description.abstract在競技體育的比賽中,雙方選手較量的不只有自己的技術,還必須考量到心理的素質與策略的使用,就像是場戰爭一樣。這些比賽資料隨著每一場的比賽不斷地增加,我們可以透過這些資料歸納分析出一個選手在面對不同對手的戰術與特色。在高水平的比賽當中,教練與選手本身都必須要清楚地了解自己與對手的優劣勢,才能夠針對選手進行適當的訓練,讓選手在比賽中能有更好的表現。
隨著資訊科技的創新與進步,的確存在許多技術是用來分析這些比賽資料。不過,在視覺化分析的領域,去探討如何將選手的特色與比賽的過程呈現給使用者的議題卻相對地乏人問津。再加上現存的比賽系統只有記錄最後的比分而已,並沒有紀錄比賽過程是如何拉鋸、和選手在不同階段時的表現。因此,受到視覺化在其他領域應用的啟發,我們針對拍類競技體育的比賽提出了一套完整的視覺化系統,設計不同層次的呈現來詮釋選手在比賽中的表現。透過我們的系統,可以經由這些圖像去了解選手在比賽不同時期的策略與戰術調整的反應,來更加了解比賽的經過與選手的特色。並且,使用者也可以將多個選手的資料進行比較,利用不同特徵的圖像來差異化和風格化每位選手,來取代現有的文字與記錄。
zh_TW
dc.description.abstractA competitive sport match is like a war between the two contestants, not only for physical skills but also mental strategies. Since large datasets are generated players every time they compete, we can use a player’s historical performance to derive his or her tactics when facing different situation and opponent. In order to win competitions at worldwide level, coaches and athletes must acquire a clear understanding of an athlete’s strength and weaknesses in skills and tactics during competitions, and this will help the athlete continue to improve and excel at the sport by training through proper way.
With the development of computer science and technology, there are some data mining techniques that help sport game analysis. However, as interesting as an athlete’s sport performance is, visualization techniques that helps people find patterns and characteristics on players’ performance is still relatively sparse. In addition, current sport statistics only record final score at game level, and the step by step performance of the player throughout the game remains hidden. Thus, inspired by information visualization techniques, we focused on racket competitive sports and proposed several representations that can help visualize an athlete’s performance in matches, like how the player earns a score. With our visualization system, we can observe all the games played by the athlete to interpret the athlete’s performance, improvement, and tactics adjusting across game-play timeline and be able to compare multiple players’ characteristics.
en
dc.description.provenanceMade available in DSpace on 2021-06-13T00:30:05Z (GMT). No. of bitstreams: 1
ntu-100-R98725020-1.pdf: 79383431 bytes, checksum: 13e371b3bb8311ff5cf709810306f47d (MD5)
Previous issue date: 2011
en
dc.description.tableofcontents致謝 ii
論文摘要 iii
Thesis Abstract iv
List of Figures vii
List of Tables xi
Chapter 1 Introduction 1
1.1 Background and Motivation 1
1.2 Research Objectives 3
Chapter 2 Related Work 4
2.1 Information Visualization 4
2.2 Text Visualization 7
2.3 Time-series and Multi-dimension Data Visualization 16
2.4 Sport Data Mining and Visualization 22
2.5 Summary 36
Chapter 3 Methodology 37
3.1 Preliminary 37
3.2 Game Representation 39
3.3 Visualizing Competitive Sports Games 40
3.3.1 Basic Ideas 40
3.3.2 The Use of Colors 41
3.3.3 Accumulation of Match 45
3.4 Interpretations 47
3.5 Game Level View 49
3.6 Summary 51
Chapter 4 Visualization Results 52
4.1 Single Game Interpretations 52
4.2 Multi-Games Aggregation Interpretations 58
4.3 Extractions by Filters 64
4.4 Comparisons between Multiple Targets 70
4.5 System Interface 73
Chapter 5 Evaluation and User Feedback 76
5.1 Evaluation Process 76
5.2 Evaluation Results 84
Chapter 6 Conclusions and Future Works 87
References 88
dc.language.isoen
dc.subject選手戰術zh_TW
dc.subject視覺化zh_TW
dc.subject視覺分析zh_TW
dc.subject競技體育zh_TW
dc.subject桌球zh_TW
dc.subjectVisual Analysisen
dc.subjectPlayer Strategyen
dc.subjectTable Tennisen
dc.subjectCompetitive Sporten
dc.subjectVisualizationen
dc.title視覺化分析拍類競技體育競賽之選手表現與策略風格zh_TW
dc.titleVisualization of racket competitive sports: providing insights on performance, style, and tactic.en
dc.typeThesis
dc.date.schoolyear99-2
dc.description.degree碩士
dc.contributor.oralexamcommittee楊傳凱,盧信銘,楊立偉
dc.subject.keyword視覺化,視覺分析,競技體育,桌球,選手戰術,zh_TW
dc.subject.keywordVisualization,Visual Analysis,Competitive Sport,Table Tennis,Player Strategy,en
dc.relation.page91
dc.rights.note有償授權
dc.date.accepted2011-08-04
dc.contributor.author-college管理學院zh_TW
dc.contributor.author-dept資訊管理學研究所zh_TW
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