Decomposing biological motion: A linear model for analysis and synthesis of human gait patterns
Nikolaus F. Troje · Journal of Vision · 2010
We present an algorithm that transforms visual motion data such that they can be successfully approached with linear methods from statistics and pattern recognition. The transformation is based on a linear decomposition of postural data into a few components that change with sinusoidal temporal patterns. The components repeat consistently across subjects such that linear combinations of existing motion data result in smooth, meaningful interpolations.