DocumentCode :
2675861
Title :
Parameterized image varieties: a novel approach to the analysis and synthesis of image sequences
Author :
Genc, Yakup ; Ponce, Jean
Author_Institution :
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
fYear :
1998
fDate :
4-7 Jan 1998
Firstpage :
11
Lastpage :
16
Abstract :
This paper addresses the problem of characterizing the space formed by all images of a rigid set of n points observed by a weak perspective or paraperspective camera. By taking explicitly into account the Euclidean constraints associated with calibrated cameras, we show that this space is a six-dimensional variety embedded in R2n, and parameterize it using the image positions of three reference points. This parameterization is constructed via linear least squares from point correspondences established across a sequence of images, and it is used to synthesize new pictures without any explicit three-dimensional model. Degenerate scene and camera configurations are analyzed, and experiments with real image sequences are presented
Keywords :
computer vision; hidden feature removal; image sequences; least mean squares methods; Euclidean constraints; calibrated cameras; camera configurations; explicit three-dimensional model; image sequences; linear least squares; parameterized image varieties; paraperspective camera; point correspondences; real image sequences; reference points; six-dimensional variety; Cameras; Computer graphics; Computer science; Functional analysis; Image analysis; Image sequence analysis; Image sequences; Layout; Least squares methods; Rendering (computer graphics);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision, 1998. Sixth International Conference on
Conference_Location :
Bombay
Print_ISBN :
81-7319-221-9
Type :
conf
DOI :
10.1109/ICCV.1998.710695
Filename :
710695
Link To Document :
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