Using Location, Bearing and Motion Data to Filter Video and System Logs

  • Alistair Morrison
  • Paul Tennent
  • John Williamson
  • Matthew Chalmers
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4480)


In evaluating and analysing a pervasive computing system, it is common to log system use and to create video recordings of users. A lot of data will often be generated, representing potentially long periods of user activity. We present a procedure to identify sections of such data that are salient given the current context of analysis; for example analysing the activity of a particular person among many trial participants recorded by multiple cameras. By augmenting the cameras used to capture a mobile experiment, we are able to establish both a location and heading for each camera, and thus model the field of view for each camera over time. Locations of trial participants are also recorded and compared against camera views, to determine which periods of user activity are likely to have been recorded in detail. Additionally the stability of a camera can be tracked and video can be subsequently filtered to exclude footage of unacceptable quality. These techniques are implemented in an extension to Replayer: a software toolkit for use in the development cycle of mobile applications. A report of initial testing is given, whereby the technique’s use is demonstrated on a representative mobile application.


Video auto-classification analysis toolkit log synchronisation visualisation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aizawa, K., Ishijima, K., Shiina, M.: Summarizing Wearable Video. In: Proceedings of International Conference on Image Processing, Thessaloniki, Greece, pp. 398–401 (2001)Google Scholar
  2. 2.
    Badre, A.N., et al.: A User Interface Evaluation Environment Using Synchronized Video, Visualizations and Event Trace Data. Software Quality Journal 4(2) (1995)Google Scholar
  3. 3.
    Barkhuus, L., Chalmers, M., Hall, M., et al.: Picking Pockets on the Lawn: The Development of Tactics and Strategies in a Mobile Game. In: Beigl, M., et al. (eds.) UbiComp 2005. LNCS, vol. 3660, pp. 358–374. Springer, Heidelberg (2005)Google Scholar
  4. 4.
    Becker, R.A., Cleveland, W.S.: Brushing Scatterplots. Technometrics 29, 127–142 (1987)CrossRefMathSciNetGoogle Scholar
  5. 5.
    Beeharee, A., Steed, A.: Filtering Location-Based Information Using Visibility. In: Proceedings of Location- and Context-Awareness, Munich, Germany, pp. 306–315 (2005)Google Scholar
  6. 6.
    Bell, M., Chalmers, M., Barkhuus, L., et al.: Interweaving Mobile Games with Everyday Life. In: Proc. ACM CHI, Montreal, pp. 417–426 (2006)Google Scholar
  7. 7.
    Chalmers, M., Galani, A.: Seamful Interweaving: Heterogeneity in the Theory and Design of Interactive Systems. In: Proceedings of ACM Symposium on Designing Interactive Systems (DIS 2004), Massachusetts, USA, pp. 243–252 (2004)Google Scholar
  8. 8.
    Yamasaki, T., et al.: Person Tracking and Multicamera Video Retrieval Using Floor Sensors in a Ubiquitous Environment. In: Leow, W.-K., et al. (eds.) CIVR 2005. LNCS, vol. 3568, pp. 297–306. Springer, Heidelberg (2005)Google Scholar
  9. 9.
    French, A., et al.: Software Replay Tools for Time-based Social Science Data. Presented at the 2nd International Conference on e-Social Science, Manchester (2006)Google Scholar
  10. 10.
    Hughes, S., Oakley, I., O’Modhrain, S.: MESH: Supporting Mobile Multi-modal Interfaces. Presented at the Seventeenth Annual ACM Symposium on User Interface Software and Technology (UIST 2004), Santa Fe, New Mexico, USA (2004)Google Scholar
  11. 11.
    McCurdy, N.J., Carlisle, J.N., Griswold, W.G.: Harnessing Mobile Ubiquitous Video. In: Proceedings of the ACM Conference on Human Factors in Computing (CHI2005), Portland, Oregon, USA, pp. 1645–1648 (2005)Google Scholar
  12. 12.
    Morrison, A., Tennent, P., Chalmers, M.: Coordinated Visualisation of Video and System Log Data. In: Proceedings of the Fourth International Conference on Coordinated & Multiple Views in Exploratory Visualization (CMV2006), London, UK, pp. 91–102 (2006)Google Scholar
  13. 13.
    Sawahata, Y., Aizawa, K., Bakker, E.M., et al.: Indexing of Personal Video Captured by a Wearable Imaging System. In: Bakker, E.M., Lew, M., Huang, T.S., Sebe, N., Zhou, X.S. (eds.) CIVR 2003. LNCS, vol. 2728, pp. 342–351. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  14. 14.
    Tennent, P., Chalmers, M.: Recording and Understanding Mobile People and Mobile Technology. In: Proceedings of the First International Conference on e-Social Science, Manchester, UK (2005)Google Scholar
  15. 15.
    Titterton, D.H., Weston, J.L.: Strapdown Inertial Navigation Technology, 2nd edn. The Institution of Electrical Engineers (2004)Google Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Alistair Morrison
    • 1
  • Paul Tennent
    • 1
  • John Williamson
    • 1
  • Matthew Chalmers
    • 1
  1. 1.Department of Computing Science, University of Glasgow, GlasgowUK

Personalised recommendations