PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Level Set Gait Analysis for Synthesis and Reconstruction
Sasan Mahmoodi
In: International Symposium on Visual Computing, 30 Nov.-4 Dec. 2009, Las Vegas, USA.


We describe a new technique to extract the boundary of a walking subject, with ability to predict movement in missing frames. This paper uses a level sets representation of the training shapes and uses an interpolating cubic spline to model the eigenmodes of implicit shapes. Our contribution is to use a continuous representation of the feature space variation with time. The experimental results demonstrate that this level set-based technique can be used reliably in reconstructing the training shapes, estimating in-between frames to help in synchronizing multiple cameras, compensating for missing training sample frames, and the recognition of subjects based on their gait

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EPrint Type:Conference or Workshop Item (Oral)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Machine Vision
ID Code:5598
Deposited By:Sasan Mahmoodi
Deposited On:08 March 2010