Real-Time Rendering System of 3D Images Using Layered Probability Maps

Abstract

We propose an image-based rendering method called “layered probability mapping.” The algorithm requires modest computer power but produces high-quality output images even from textureless or noisy input images. Thus, real-time applications, such as immersive teleconferencing and live broadcasting, are promising areas of use. The key idea is a layered probability map representation using a set of two-dimensional probabilistic functions. This takes into account ambiguities regarding object depth. To test the feasibility of this method, we developed a prototype system with nine synchronized cameras and a thirteen-PC cluster. By calculating the algorithm in parallel, we obtained stable 5-15FPS image generation without any off-line procedures between the image capture and the display.