Approximating the reachable space of human walking paths: a low dimensional linear approach

In this work, we aim to exhibit the geometrical shape primitives of human walking trajectories using a statistical model constructed through Principal Component Analysis. This analysis provides sufficient information to derive a linear human-like path generator based on examples. The examples are provided by a motion capture database of human walking trajectories. The proposed model captures the shape of trajectories in terms of path length and deformation. We have successfully applied our model to compute a good approximation of the reachable space of human walking. This can be done with a negligible computational cost since it is based on a linear combination of basis human paths.