DocumentCode
984107
Title
Algebraic methods for image processing and computer vision
Author
Holt, Robert J. ; Huang, Thomas S. ; Netravali, Arun N.
Author_Institution
AT&T Bell Labs., Murray Hill, NJ, USA
Volume
5
Issue
6
fYear
1996
fDate
6/1/1996 12:00:00 AM
Firstpage
976
Lastpage
986
Abstract
Many important problems in image processing and computer vision can be formulated as the solution of a system of simultaneous polynomial equations. Crucial issues include the uniqueness of solution and the number of solutions (if not unique), and how to find numerically all the solutions. The goal of this paper is to introduce to engineers and scientists some mathematical tools from algebraic geometry which are very useful in resolving these issues. Three-dimensional motion/structure estimation is used as the context. However, these tools should also be helpful in other areas including surface intersection in computer-aided design, and inverse position problems in kinematics/robotics. The tools to be described are Bezout numbers, Grobner bases, homotopy methods, and a powerful theorem which states that under rather general conditions one can draw general conclusions on the number of solutions of a polynomial system from a single numerical example
Keywords
CAD; computational geometry; computer vision; inverse problems; kinematics; mobile robots; motion estimation; polynomials; robot vision; 3D motion estimation; 3D motion structure; Bezout numbers; Grobner bases; algebraic geometry; algebraic methods; computer vision; computer-aided design; homotopy methods; image processing; inverse position problems; kinematics; robotics; simultaneous polynomial equations; surface intersection; uniqueness; Collision avoidance; Computational geometry; Computer vision; Design automation; Equations; Image processing; Image sequences; Motion estimation; Polynomials; Robot kinematics;
fLanguage
English
Journal_Title
Image Processing, IEEE Transactions on
Publisher
ieee
ISSN
1057-7149
Type
jour
DOI
10.1109/83.503913
Filename
503913
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