PCA-based walking engine using motion capture data

Abstract

This paper aims to propose a novel approach to generate new generic human walking patterns using motion-captured data, leading to a real-time engine intended for virtual humans animation. The method applies the PCA (principal component analysis) technique on motion data acquired by an optical system to yield a reduced dimension space where not only interpolation, but also extrapolation are possible, controlled by quantitative speed parameter values. Moreover, with proper normalization and time warping methods, the generic presented engine can produce walking motions with continuously varying human height and speed with real-time reactivity