Filtering Motion Data Through Piecewise Polynomial Approximation
Vittorio Lippi*, Carlo Alberto Avizzano* and Emanuele Ruffaldi*
In this work we propose a system to ﬁlter human movement data and store them into a compact representation. We are interested both in noise reduction and in segmentation. The method described in this paper relies on a iterative optimization and guarantee to converge to a local optimum: it proved anyway to produce stable results and to provide an accurate segmentation on the analyzed data . We analyze the Three ball cascade Juggling as case study: This provides us the challenge to represent both low-pass dynamics of human limbs and juggled balls and the discontinuities produced by contact forces.
© Owned by the authors, published by EDP Sciences, 2011