DocumentCode :
1043265
Title :
Describing complicated objects by implicit polynomials
Author :
Keren, Daniel ; Cooper, David ; Subrahmonia, Jayashree
Author_Institution :
Lab. for Eng. Man/Machine Syst., Brown Univ., Providence, RI, USA
Volume :
16
Issue :
1
fYear :
1994
fDate :
1/1/1994 12:00:00 AM
Firstpage :
38
Lastpage :
53
Abstract :
This paper introduces and focuses on two problems. First is the representation power of closed implicit polynomials of modest degree for curves in 2-D images and surfaces in 3-D range data. Super quadrics are a small subset of object boundaries that are well fitted by these polynomials. The second problem is the stable computationally efficient fitting of noisy data by closed implicit polynomial curves and surfaces. The attractive features of these polynomials for Vision is discussed
Keywords :
computer vision; curve fitting; image processing; image segmentation; polynomials; 2-D images; 3-D range data; closed implicit polynomials; complicated objects; implicit polynomials; noisy data; object boundaries; representation power; super quadrics; surfaces; vision; Curve fitting; Laboratories; Man machine systems; Noise robustness; Object recognition; Polynomials; Shape; Solid modeling; Surface fitting; Systems engineering and theory;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.273718
Filename :
273718
Link To Document :
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