The proposal of model-based initial frame alignment using real-coded GA for mixed reality

Abstract

In this paper, we propose a model-based alignment system using real-coded genetic algorithm (RGA) for mixed reality (MR) or augmented reality (AR). MR/AR is a technique for superimposing useful virtual information on the real world to provide users more effective views. To realize the MR/AR, the alignment between real space and virtual space is a serious problem. In particular, an initial frame alignment for real-time tracking is needed in the previous knowledge based MR/AR. Therefore, we propose an initial frame alignment method using RGA. In this paper, we use the multiple RGA generation alternation models, crossovers, and mutations to design an optimum GA for the alignment system. This paper shows the expanding version of the pre-proposed method by our system. In order to show the effectiveness of proposed method, we perform some matching simulations when we applied to the real space.