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Sea of Images: A Dense Sampling Approach for Rendering Large Indoor Environments
IEEE Computer Graphics & Applications, November 2003

Daniel Aliaga, Thomas Funkhouser, Dimah Yanovsky,
Ingrid Carlbom


Visual simulation of large real-world environments is one of the grand challenges of computer graphics. Applications include remote education, virtual heritage, specialist training, electronic commerce, and entertainment. In this paper, we present a “Sea of Images,” an image-based approach to providing interactive and photorealistic walkthroughs of complex indoor environments. Our strategy is to obtain a dense sampling of viewpoints in a large static environment with omnidirectional images. We use a motorized cart to capture omnidirectional images every few inches on an eye-height plane throughout an environment. We then compress and store the images in a multiresolution hierarchy suitable for real-time prefetching to produce interactive walkthroughs. Finally, we render novel images for a simulated observer viewpoint using a feature-based warping algorithm. Our system acquires and preprocesses over 15,000 images covering more than 1000 square feet of environment space with the average distance from a random point on the eye-height plane to a captured image being 1.5 inches. The average capture and processing time is 7 hours. We demonstrate photorealistic walkthroughs of real-world environments reproducing specular reflections and occlusion effects while rendering 20-30 frames per second.

Citation (BibTeX)

Daniel Aliaga, Thomas Funkhouser, Dimah Yanovsky, and Ingrid Carlbom. Sea of Images: A Dense Sampling Approach for Rendering Large Indoor Environments. IEEE Computer Graphics & Applications 23(6), November 2003.

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