We generated a high resolution 3D object using a commercial DSLR camera and the low depth information of Kinect. High resolution depth map was obtained through camera calibration between the DSLR and Kinect sensor. 3D mesh model was created by the high resolution depth information and mapped with RGB color value. The experimental result showed that it is possible to create high resolution 3D object from the depth camera. This paper is expected to be applied to reality game graphic.

In this paper, we present a practical palce and object recognition method for guiding visitors in building environments. Recognizing palces or objects in real world can be a difficult problem due to motion blur and camera noise. In this work, we present a modeling method based on the bidirectional interactionbetween places and objects for simulataneous reinforcement for the robust recognition. The unification of visual context including scene context, object context, and temporal context is also. The proposed system has been tested to guide visitors in a large scale building environment(10 topological places, 80 3D objects)