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Image-based rendering using parameterized image varieties

delete2001-01-01
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PRE
AI
Y
Yakup Genç
J
Jean Ponce
DOI:10.1023/A:1011114903748delete
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Abstract

Abstract

En 中文
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.
Keywords:
image-based rendering
parameterized image varieties
weak perspective and paraperspective projections
motion analysis
multi-view geometry
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Journal

International Journal of Computer Vision cover
International Journal of Computer Vision
IF:
9.3
Papers:
3.9K
Citations:
2.8W

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