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.

Double Cross Cylinder (DCC) is an object created by intersecting the cylinder of Y-axis and the cylinder of the Z-axis. DCC mapping is a new method for effectively mapping the environment. This method eliminates the singularity effect caused in the environment maps and shows an almost even amount of area for the environment occupied by a single texel. The surrounding environment can also be stored more effectively through more accurate sampling. Improvement is also achieved in the rendering time of the DCC mapping method and octahedral mapping method based on DCC mapping. Therefore, the DCC mapping method is suitable to be applied on environment navigation systems due to its effective storage of the environment and faster sampling time.

We have studied an image acquisition system for a real-time image- based rendering (IBR) system. In this area, most conventional systems sacrifice spatial or temporal resolution for a large number of input images. However, only a portion of the image data is needed for rendering, and the portion required is determined by the position of the imaginary viewpoint. In this paper, we propose an acquisition system for a real-time image-based rendering system that uses pixel-based random-access image sensors to eliminate the main bottleneck in conventional systems. We have developed a prototype CMOS image sensor, which has 128 128 pixels. We verified the prototype chip's selective readout function. We also verified the sample & hold feature.