This paper presents a grid-based, real-time surface modeling algorithm in which the generation of a precise 3D model is possible by considering the user's intention during the course of the spatial input. In order to create the corresponding model according to the user's input data, plausible candidates of wand traversal patterns of grid edges are defined by considering the sequential and directional characteristics of the wand input. The continuity of the connected polygonal surfaces, including the octree space partitioning, is guaranteed without the extra crack-patching algorithm and the pre-defined patterns. Furthermore, the proposed system was shown to be a suitable and effective surface generation tool for the spatial sketching system. It is not possible to implement the unusual input intention of the 3D spatial sketching system using the conventional Marching Cubes algorithm.

We have developed a visual entertainment system called "Future Cast" which enables anyone to easily participate in a pre-recorded or pre-created film as an instant CG movie star. This system provides audiences with the amazing opportunity to join the cast of a movie in real-time. The Future Cast System can automatically perform all the processes required to make this possible, from capturing participants' facial characteristics to rendering them into the movie. Our system can also be applied to any movie created using the same production process. We conducted our first experimental trial demonstration of the Future Cast System at the Mitsui-Toshiba pavilion at the 2005 World Exposition in Aichi Japan.

In this paper, we propose a new technique to generate virtual views of three-dimensional (3D) models. The technique is implemented into our facial pose transformation system, which takes only one frontal image and transforms it into virtual views. In our system, to overcome the complex of 3D geometric model, Image Based Rendering based algorithm and mesh-based methods are applied. We also introduce our new Invertible Meshwarp Algorithm, which is developed based on Two-pass Meshwarp Algorithm. Firstly, in the system, for any given person, we take a frontal face image to compose a frontal mesh for it. The standard mesh set of a specific person is created for several face sides; front, half left, half right, left and right side. The other meshes are then automatically generated based on the standard mesh set and the frontal mesh. Continually, we use Invertible Meshwarp Algorithm, which improvably solves the overlap or inversion of neighbor vertices of those created meshes. This step will finalize the generation of different views or the virtual looks of the frontal face image. We then evaluate our transformation system performance by comparing the normalized distance between several feature points in the real and transformed face images. The system is built based on C/C++ language and our result shows that the average error in the feature location is about 7% of the distance from the center of both eyes to the center of a mouth between the actual and transformed face images.

In the past decade, significant effort has been made toward increasing the accuracy and robustness of three-dimensional scanning methods. In this paper, we present a new prototype vision system named 3D Model Studio, which has been built to reconstruct a complete 3D model in as less as a few minutes. New schemes for a probe calibration and a 3D data merging (axis consolidation) are employed. We also propose a new semi-automatic contour registration method to generate accurate contour model from 3D data points, along with a contour triangulation based surface reconstruction. Experimental result shows that our system works well for reconstructing a complete 3D surface model of a human body.