Real-time capture and reconstruction system with multiple GPUs for a 3D live scene by a generation from 4K IP images to 8K holograms

We developed a real-time capture and reconstruction system for three-dimensional (3D) live scenes. In previous research, we used integral photography (IP) to capture 3D images and then generated holograms from the IP images to implement a real-time reconstruction system. In this paper, we use a 4K (3,840 x 2,160) camera to capture IP images and 8K (7,680 x 4,320) liquid crystal display (LCD) panels for the reconstruction of holograms. We investigate two methods for enlarging the 4K images that were captured by integral photography to 8K images. One of the methods increases the number of pixels of each elemental image. The other increases the number of elemental images. In addition, we developed a personal computer (PC) cluster system with graphics processing units (GPUs) for the enlargement of IP images and the generation of holograms from the IP images using fast Fourier transform (FFT). We used the Compute Unified Device Architecture (CUDA) as the development environment for the GPUs. The Fast Fourier transform is performed using the CUFFT (CUDA FFT) library. As a result, we developed an integrated system for performing all processing from the capture to the reconstruction of 3D images by using these components and successfully used this system to reconstruct a 3D live scene at 12 frames per second. (C) 2012 Optical Society of America