Camera pose estimation with respect to target scenes is an important technology for superimposing virtual information in augmented reality (AR). However, it is difficult to estimate the camera pose for all possible view angles because feature descriptors such as SIFT are not completely invariant from every perspective. We propose a novel method of robust… (More)
Given a time series data, model dynamical systems are built using a hierarchical Bayesian scheme with feedforward neural nets and then the models are compared in terms of marginal likelihood. The model with the highest marginal likelihood is used for predictions. The algorithm is applied to building airconditioning load prediction .