Ellipse Constraints for Improved Wide-Baseline Feature Matching and Reconstruction

被引:0
|
作者
Ruess, Dominik [1 ]
Reulke, Ralf [2 ]
机构
[1] Deutsch Zentrum Luft & Raumfahrt eV, Helmholtz Gemeinschaft, Inst Robot & Mechatron, Opt Informat Syst, Rutherfordstr 2, D-12489 Berlin, Germany
[2] Humboldt Univ, Inst Informat, Comp Vis, Berlin, Germany
来源
COMBINATORIAL IMAGE ANALYSIS | 2011年 / 6636卷
关键词
Key Points; Feature Regions; Ellipses; Feature Matching; Epipolar Constraints; Reconstruction; GEOMETRY; CALIBRATION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The classic feature matching process has two drawbacks. Firstly, ambiguous but possibly correct matches will potentially be removed and secondly, there is no constraint for the 2D size of the features. In the present paper these drawbacks are tackled at once with a different approach: by considering region features instead of point features and by adding constraints based on the features' shape. Here, the shape will be described with an ellipse. Using existing knowledge about the algebraic properties of ellipses within the computer vision domain, this enables additional constraints such as ellipse tangents. The number of ambiguous matches is reduced and increased control of the physical 2D size of the features is obtained. This will be shown on known epipolar geometry. Additionally, reconstruction of feature ellipses is examined.
引用
收藏
页码:168 / 181
页数:14
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