DocumentCode :
178743
Title :
Euclidean Structure from Conic Feature Correspondences
Author :
Zijian Zhao
Author_Institution :
Sch. of Control Sci. & Eng., Shandong Univ., Jinan, China
fYear :
2014
fDate :
24-28 Aug. 2014
Firstpage :
4010
Lastpage :
4014
Abstract :
In this paper, a novel method of the 2D Euclidean structure recovery in one view from the projections of N parallel conics is proposed. Without considering the conic dual to the absolute points (CDAP), we transform conic features from the homogeneous coordinates to the lifted coordinates. In the lifted space, the conic features have the similar properties to the point or line features, which especially means that the Homography can also be deduced by conic features directly. Our work gives a generic framework of recovering the Euclidean structure from conic features. A series of experiments with simulated and real data are conducted. The experimental results show that the proposed theory has its validity in practical applications.
Keywords :
cameras; feature extraction; 2D Euclidean structure recovery; CDAP; N-parallel conic projections; conic dual-to-the-absolute points; conic feature correspondences; conic features; generic framework; homogeneous coordinates; homography; lifted coordinates; lifted space; line features; point features; Calibration; Cameras; Computer vision; Equations; Symmetric matrices; Transmission line matrix methods; Vectors; Euclidean structure; camera calibration; conic correspondence; homography;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2014 22nd International Conference on
Conference_Location :
Stockholm
ISSN :
1051-4651
Type :
conf
DOI :
10.1109/ICPR.2014.687
Filename :
6977400
Link To Document :
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