Upgrading eigenspace-based prediction using null space and its application to path prediction

This paper proposes a method for an Eigenspace-based prediction of a vector with missing components by modifying a projection of conventional Eigenspace method, and demonstrates the application to the prediction of the path of a walking person. This modification is based on domain-specific knowledge of data, and a linear combination of vectors in the null space of Eigenspace is added so that a cost function of smoothness of path is minimized. Some experimental results on actual paths are shown to demonstrate how the proposed method works

Upgrading eigenspace-based prediction using null space and its application to path prediction

Subspace 2007 Workshop on ACCV2007, poster and slide ; Place : Tokyo, Japan ; Date : November 19, 200