A proposal of model-based alignment using swarm intelligence and condensation
In this paper, we propose a model-based alignment system using swarm intelligence and condensation for mixed reality (MR) and augmented reality (AR). MR and AR are techniques to overlay useful virtual information on the real world and display them to provide users more effective views. To realize the MR and AR, 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 alignment. Therefore, we propose an alignment method using swarm intelligence for the initial frame alignment. In this paper, we use the multiple swarm intelligence methods for designing an effective method of alignment system. This paper shows the expanding version of the pre-proposed method by our system. Moreover, we conduct tracking of the alignment target using condensation based on the initial frame alignment results. By using this system, a model-based alignment can be conducted in a room-type environment such as being hard to acquire many feature points. In order to show the effectiveness of a proposed method, we perform some alignment experiments when we applied the alignment system to a real space.