Bring it to the pitch: Combining video and movement data to enhance team sport analysis M Stein, H Janetzko, A Lamprecht, T Breitkreutz, P Zimmermann, ... IEEE transactions on visualization and computer graphics 24 (1), 13-22, 2017 | 200 | 2017 |
Visual opinion analysis of customer feedback data D Oelke, M Hao, C Rohrdantz, DA Keim, U Dayal, LE Haug, H Janetzko 2009 IEEE symposium on visual analytics science and technology, 187-194, 2009 | 159 | 2009 |
Generalized scatter plots DA Keim, MC Hao, U Dayal, H Janetzko, P Bak Information Visualization 9 (4), 301-311, 2010 | 155 | 2010 |
Anomaly detection for visual analytics of power consumption data H Janetzko, F Stoffel, S Mittelstädt, DA Keim Computers & Graphics 38, 27-37, 2014 | 146 | 2014 |
Feature-driven visual analytics of soccer data H Janetzko, D Sacha, M Stein, T Schreck, DA Keim, O Deussen Visual Analytics Science and Technology (VAST), 2014 IEEE Conference on, 13-22, 2014 | 123* | 2014 |
Visual sentiment analysis on twitter data streams M Hao, C Rohrdantz, H Janetzko, U Dayal, DA Keim, LE Haug, MC Hsu 2011 IEEE conference on visual analytics science and technology (VAST), 277-278, 2011 | 114 | 2011 |
How to make sense of team sport data: From acquisition to data modeling and research aspects M Stein, H Janetzko, D Seebacher, A Jäger, M Nagel, J Hölsch, S Kosub, ... Data 2 (1), 2, 2017 | 111 | 2017 |
Spatiotemporal analysis of sensor logs using growth ring maps P Bak, F Mansmann, H Janetzko, D Keim IEEE transactions on visualization and computer graphics 15 (6), 913-920, 2009 | 93 | 2009 |
Director's Cut: Analysis and Annotation of Soccer Matches M Stein, H Janetzko, T Breitkreutz, D Seebacher, T Schreck, ... IEEE Computer Graphics and Applications 36 (5), 50-60, 2016 | 79 | 2016 |
Visual sentiment analysis of customer feedback streams using geo-temporal term associations MC Hao, C Rohrdantz, H Janetzko, DA Keim, U Dayal, LE Haug, M Hsu, ... Information Visualization 12 (3-4), 273-290, 2013 | 57 | 2013 |
Visual exploration of frequent patterns in multivariate time series MC Hao, M Marwah, H Janetzko, U Dayal, DA Keim, D Patnaik, ... Information Visualization 11 (1), 71-83, 2012 | 55 | 2012 |
Visual soccer analytics: Understanding the characteristics of collective team movement based on feature-driven analysis and abstraction M Stein, J Häu©¬ler, D Jäckle, H Janetzko, T Schreck, DA Keim ISPRS International Journal of Geo-Information 4 (4), 2159-2184, 2015 | 54 | 2015 |
Dynamic visual abstraction of soccer movement D Sacha, F Al‐Masoudi, M Stein, T Schreck, DA Keim, G Andrienko, ... Computer Graphics Forum 36 (3), 305-315, 2017 | 53 | 2017 |
A visual analytics approach for peak‐preserving prediction of large seasonal time series MC Hao, H Janetzko, S Mittelstädt, W Hill, U Dayal, DA Keim, M Marwah, ... Computer Graphics Forum 30 (3), 691-700, 2011 | 51 | 2011 |
Visual boosting in pixel‐based visualizations D Oelke, H Janetzko, S Simon, K Neuhaus, DA Keim Computer Graphics Forum 30 (3), 871-880, 2011 | 50 | 2011 |
Exploration through enrichment: a visual analytics approach for animal movement D Spretke, P Bak, H Janetzko, B Kranstauber, F Mansmann, S Davidson Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances ¡¦, 2011 | 45 | 2011 |
SimpliFly: A methodology for simplification and thematic enhancement of trajectories K Vrotsou, H Janetzko, C Navarra, G Fuchs, D Spretke, F Mansmann, ... IEEE Transactions on Visualization and Computer Graphics 21 (1), 107-121, 2014 | 40 | 2014 |
Computing predicted data according to weighted peak preservation and time distance biasing MC Hao, U Dayal, D Keim, W Hill, S Mittelstädt, H Janetzko US Patent 9,355,357, 2016 | 37 | 2016 |
Visual analytics for exploring local impact of air traffic J Buchmüller, H Janetzko, G Andrienko, N Andrienko, G Fuchs, DA Keim Computer Graphics Forum 34 (3), 181-190, 2015 | 36 | 2015 |
Enhancing parallel coordinates: Statistical visualizations for analyzing soccer data H Janetzko, M Stein, D Sacha, T Schreck Electronic Imaging 2016 (1), 1-8, 2016 | 33 | 2016 |