Image-Based Rendering Using Parameterized Image Varieties |
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Authors: | Genc Yakup Ponce Jean |
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Affiliation: | (1) Imaging and Visualization Department, Siemens Corporate Research, Inc., Princeton, NJ 08540, USA;(2) Department of Computer Science and Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA |
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Abstract: | This paper addresses the problem of characterizing the set of all images of a rigid set of m points and n lines observed by a weak perspective or paraperspective camera. By taking explicitly into account the Euclidean constraints associated with calibrated cameras, we show that the corresponding image space can be represented by a six-dimensional variety embedded in R2(m+n) and parameterized by the image positions of three reference points. The coefficients defining this parameterized image variety (or PIV for short) can be estimated from a sample of images of a scene via linear and non-linear least squares. The PIV provides an integrated framework for using both point and line features to synthesize new images from a set of pre-recorded pictures (image-based rendering). The proposed technique does not perform any explicit three-dimensional scene reconstruction but it supports hidden-surface elimination, texture mapping and interactive image synthesis at frame rate on ordinary PCs. It has been implemented and extensively tested on real data sets. |
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Keywords: | Image-based rendering parameterized image varieties weak perspective and paraperspective projections motion analysis multi-view geometry |
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