NDLI: Minimal projective reconstruction with missing data

Content Provider	IEEE Xplore Digital Library
Author	Long Quan Heyden, A. Kahl, F.
Copyright Year	1999
Description	Author affiliation: CNRS, INRS, Montbonnot St. Martin, France (Long Quan)
Abstract	The minimal data necessary for projective reconstruction from point correspondences is well-known when the points are visible in all images. In this paper, we formulate and propose solutions to a new family of reconstruction problems from multiple images with minimal data, where there are missing points in some of the images. The ability to handle the minimal cases with missing data is of great theoretical and practical importance. It is unavoidable to use them to bootstrap robust estimation such as RANSAC and LMS algorithms and optimal estimation such as bundle adjustment. First, we develop a framework to parametrize the multiple view geometry, needed to handle the missing data cases. Then we present a solution to the minimal case of 8 points in 3 images, where one of the points is missing in one of the three images. We prove that there are in general as many as 11 solutions for this minimal case. Furthermore, all minimal cases with missing data for 3 and 4 in images are catalogued. Finally we demonstrate the method on both simulated and real images and show that the algorithms presented in this paper can be used for practical problems.
Starting Page	210
Ending Page	216
File Size	571044
Page Count	7
File Format	PDF
ISBN	0769501494
ISSN	10636919
DOI	10.1109/CVPR.1999.784631
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-06-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Cameras Robustness Least squares approximation Geometry Computer vision Computational modeling Computer simulation Reconstruction algorithms Equations
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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