Video Visualization

Creating new visual representations to extract meaningful information

The e-Research Centre is an internationally-recognized centre of excellence in the area of video visualization - the creation of new visual representations from an input video to reveal important features and events in the video. It typically extracts meaningful information from a video and conveys the extracted information to users in abstract or summary visual representations, which are typically more compact than the input video itself.

Video visualization is not intended to provide fully automatic solutions to the problem of making decisions about the contents of a video. Instead, it aims at offering a tool to assist users in their intelligent reasoning while removing the burden of viewing videos.

In particular, it can be used to fill in many gaps in practice where automated computer vision is yet to provide usable solutions. This aim justifies deviation from the creation of realistic imagery, and allows simplifications and embellishments, to improve the understanding of the input video.

Video data is inherently a form of volumetric data, and it also exhibits some flow-like features, such as motion flows. There have been many tutorials on the advances in volume visualization since 1980s, and those in flow visualization since 1990s. Despite that video data is more abundant and ubiquitous than medical imaging data, or flow simulation data, there has not been any educational programmes on video visualization. This is rather incompatible with the fact that the rapid advance of digital recording and creation technologies has resulted in an explosion of video data. As visual search through videos is time-consuming, often tedious, and mostly involves watching videos repeatedly, there is a real urgency to engage more researchers in developing new techniques for visualizing videos.

The development of video visualization started in early 2000s, which saw the emergence of a collection of novel visual designs that allow viewers to gain an insight about a video rapidly, usually without the need for watching the video. Recently, visual analytics techniques have been applied to the process of video analysis, ranging from interactive exploration to interactive construction of classifiers. The use of video visualization has also been extended from security and entertainment applications to sports and biomedical applications.

To find more about video visualization, please browse through the following references or simply contact us .


  • G.W. Daniel and M. Chen, Video visualization , Proc. IEEE Visualization 2003 , 409-416, Seattle, WA, October 2003.
  • R. P. Botchen, M. Chen, D. Weiskopf and T. Ertl, GPU-based multi-field video volume visualization , Proc. Volume Graphics , 47-54, Boston, MA, July, 2006.
  • M. Chen, R.P. Botchen, R.R. Hashim, D. Weiskopf, T. Ertl and I.M. Thornton, Visual signatures in video visualization , IEEE Transactions on Visualization and Computer Graphics , 12(5):1093-1100, 2006.
  • R. P. Botchen, S. Bachthaler, F. Schick, M. Chen, G. Mori, D. Weiskopf and T. Ertl, Action-based multi-field video visualization , IEEE Transactions on Visualization and Computer Graphics , 14(4):885-899, 2008.
  • M. Höferlin, E. Grundy, R. Borgo, D. Weiskopf, M. Chen, I. W. Griffiths and W. Griffiths, Video visualization for snooker skill training , Computer Graphics Forum , 29(3):1053-1062, 2010.
  • H. Jänicke, R. Borgo, J. S. D. Mason and M. Chen, SoundRiver: Semantically-rich sound illustration , Computer Graphics Forum , 29(2):357-366, 2010.
  • P. A. Legg, M. L. Parry, D. H. S. Chung, M. R. Jiang, A. Morris, I. W. Griffiths, D. Marshall and M. Chen. Intelligent filtering by semantic importance for single-view 3D reconstruction from Snooker video . Proc. IEEE International Conference on Image Processing (ICIP), 2433-2436, 2011.
  • M. L. Parry, P. A. Legg, D. H. S. Chung, I. W. Griffiths, M. Chen, Hierarchical event selection for video storyboards with a case study on snooker video visualization , IEEE Transactions on Visualization and Computer Graphics , 17(12):1747-1756, 2011.
  • G. K. L. Tam, H. Fang, A. J. Aubrey, P. W. Grant, P. L. Rosin, D. Marshall and M. Chen, Visualization of time-series data in parameter space for understanding facial dynamics , Computer Graphics Forum , 30(3):901-910, 2011.
  • R. Borgo., M. Chen, B. Daubney, E. Grundy, H. Jänicke, G. Heidemann, B. Höferlin, M. Höferlin, D. Weiskopf and X. Xie, State of the art report on video-based graphics and video visualization , Computer Graphics Forum , 31(8):2450-2477, 2012.
  • P. Legg, D. Chung, M. Parry, M. Jones, R. Long, I. Griffiths and M. Chen, MatchPad: Interactive glyph-based visualization for real-time sports performance analysis , Computer Graphics Forum , 31(3):1255-1264, 2012.
  • P. A. Legg, D. H. S. Chung, M. L. Parry, R. Bown, M. W. Jones, I. W. Griffiths, M. Chen, Transformation of an uncertain video search pipeline to a sketch-based visual analytics loop , IEEE Transactions on Visualization and Computer Graphics , 19(12):2109-2118, 2013.
  • R. Borgo, M. Chen, M. Hoeferlin, K. Kurzhals, P. Legg, S. Walton and D. Weiskopf, EG2013 Tutorial on Video Visualization , Eurographics Tutorial Programme , 2013.
  • R. Borgo, M. Chen, K. Kurzhals, P. Legg, S. Walton and D. Weiskopf, IEEE VIS Tutorial on Video Visualization , 2013.
  • S. Walton, K. Berger, D. Ebert and M. Chen, Vehicle object retargeting from dynamic traffic videos for real-time visualisation , to appear in The Visual Computer , Springer. Oonline version is available from September 2013.
  • B. Duffy, J. Thiyagalingam, S. Walton, D. J. Smith, A. Trefethen, J. C. Kirkman-Brown, E. A. Gaffney and M. Chen, Glyph-Based Video Visualization for Semen Analysis , to appear in IEEE Transactions on Visualization and Computer Graphics .
  • D. H.S. Chung, M. L. Parry, P. A. Legg, I. W. Griffiths, R. S. Laramee, and M. Chen, Visualizing Multiple Error-Sensitivity Fields for Single Camera Positioning , to appear in Computing and Visualization in Science .