Filtering motion capture data for real-time applications

2013-05-27-DSCN7126We have three papers from our fourMs group at this year’s NIME conference in Daejeon. The first one was presented today by Ståle Skogstad, and is based on his work on trying minimize the delay when filtering motion capture data.

Filtering motion capture data for real-time applications


In this paper we present some custom designed filters for real-time motion capture applications. Our target application is motion controllers, i.e. systems that interpret hand motion for musical interaction. In earlier research we found effective methods to design nearly optimal filters for realtime applications. However, to be able to design suitable filters for our target application, it is necessary to establish the typical frequency content of the motion capture data we want to filter. This will again allow us to determine a reasonable cutoff frequency for the filters. We have therefore conducted an experiment in which we recorded the hand motion of 20 subjects. The frequency spectra of these data together with a method similar to the residual analysis method were then used to determine reasonable cutoff frequencies. Based on this experiment, we propose three cutoff frequencies for different scenarios and filtering needs: 5, 10 and 15 Hz, which correspond to heavy, medium and light filtering, respectively. Finally, we propose a range of real-time filters applicable to motion controllers. In particular, low-pass filters and low-pass differentiators of degrees one and two, which in our experience are the most useful filters for our target application.

Skogstad, S. A., Nymoen, K., Høvin, M., Holm, S., and Jensenius, A. R. (2013). Filtering motion capture data for real-time applications. In Proceedings of the International Conference on New Interfaces For Musical Expression, pages 196–197, Daejeon, Korea.


   Address = {Daejeon, Korea},
   Author = {Skogstad, St{\aa}le A. and Nymoen, Kristian and Hovin, Mats and Holm, Sverre and Jensenius, Alexander Refsum},
   Booktitle = {Proceedings of the International Conference on New Interfaces For Musical Expression},
   Pages = {196--197},
   Title = {Filtering Motion Capture Data for Real-Time Applications},
   Year = {2013}


Published by


Alexander Refsum Jensenius is a music researcher and research musician living in Oslo, Norway.

One thought on “Filtering motion capture data for real-time applications”

Comments are closed.