The Visual Computer

, Volume 29, Issue 1, pp 7–26 | Cite as

Real-time marker prediction and CoR estimation in optical motion capture

  • Andreas Aristidou
  • Joan Lasenby
Original Article


Optical motion capture systems suffer from marker occlusions resulting in loss of useful information. This paper addresses the problem of real-time joint localisation of legged skeletons in the presence of such missing data. The data is assumed to be labelled 3d marker positions from a motion capture system. An integrated framework is presented which predicts the occluded marker positions using a Variable Turn Model within an Unscented Kalman filter. Inferred information from neighbouring markers is used as observation states; these constraints are efficient, simple, and real-time implementable. This work also takes advantage of the common case that missing markers are still visible to a single camera, by combining predictions with under-determined positions, resulting in more accurate predictions. An Inverse Kinematics technique is then applied ensuring that the bone lengths remain constant over time; the system can thereby maintain a continuous data-flow. The marker and Centre of Rotation (CoR) positions can be calculated with high accuracy even in cases where markers are occluded for a long period of time. Our methodology is tested against some of the most popular methods for marker prediction and the results confirm that our approach outperforms these methods in estimating both marker and CoR positions.


Computer vision Filtering Marker prediction Joint localisation Motion capture Inverse kinematics 

Supplementary material

(AVI 21.9 MB)


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Department of EngineeringUniversity of CambridgeCambridgeUK

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