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Viewpoint invariant exemplar-based 3D human tracking
Authors:Eng-Jon Ong   Antonio S. Micilotta   Richard Bowden  Adrian Hilton
Affiliation:aCentre for Vision, Speech and Signal Processing, SEPS, University of Surrey, Guildford GU2 7XH, Surrey, UK
Abstract:This paper proposes a clustered exemplar-based model for performing viewpoint invariant tracking of the 3D motion of a human subject from a single camera. Each exemplar is associated with multiple view visual information of a person and the corresponding 3D skeletal pose. The visual information takes the form of contours obtained from different viewpoints around the subject. The inclusion of multi-view information is important for two reasons: viewpoint invariance; and generalisation to novel motions. Visual tracking of human motion is performed using a particle filter coupled to the dynamics of human movement represented by the exemplar-based model. Dynamics are modelled by clustering 3D skeletal motions with similar movement and encoding the flow both within and between clusters. Results of single view tracking demonstrate that the exemplar-based models incorporating dynamics generalise to viewpoint invariant tracking of novel movements.
Keywords:Exemplar-based   3D human tracking   View-invariant   Learnt motion model
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