Taiki Fuji

Furniture layout AR application using floor plans based on planar object tracking

In this paper, we propose a new approach of Augmented Reality (AR) system for the furniture layout based on a planar object tracking. The planar object tracking methods using natural features are effective methods to estimate the objects pose and position in the AR applications because we are able to use the natural images. However, most of the feature descriptors have a lot of matching procedure. Therefore, by using an efficient feature point descriptor which is very fast both to build and to match, we track the planar objects. Especially, we use floor plans as the planar objects, and then furniture CG models are overlaid on the floor plans. This is because the floor plans are presented in the selection of rooms for rent or buy. Therefore, this system helps borrowers and buyers to select some mansion or apartment rooms. In this system, we propose to use human whistle sounds and color rectangles recognition to operate the furniture layout. In order to show the effectiveness of our proposed system, we perform some planar object tracking experiments when we applied the proposed system to some floor plans.

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

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.

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.

Aligning the real space with the model on see-through typed HMD for mixed reality

In this paper, we propose an approach to align the real space with the three-dimensional (3D) model for outdoor wearable mixed reality (MR) system. In our approach, we use a monocular see-through typed head-mounted display (ST-HMD) and a virtual reality (VR) sensor. We can measure six degree-of-freedom (6DOF) using this sensor. In the default setting, it is difficult and burden for people to handle the 3D model using air mouse. Therefore, we reduce the burden by automating the default setting. Moreover, when the user changes the viewpoint, we need to change the computer graphics (CG) model on ST-HMD with corresponding to the real objects of the difference in vision. We obtain the translation and rotation data from VR sensor to reflect the CG model. Then, we structured the alignment system in this system. Furthermore, in order to evaluate the proposed alignment for three-dimensional (3D) model, we show some results of the wearable aligning system using the 3D model.