DocumentCode :
2650076
Title :
Scale Assignment for Imbalanced Points
Author :
Li, Qi
fYear :
2011
fDate :
7-9 Nov. 2011
Firstpage :
197
Lastpage :
204
Abstract :
Imbalance oriented candidate selection was introduced as an alternative of non-maximum suppression, aiming to improve the localization accuracy. To distinguish interest points detected via non-maximum suppression, we call interest points detected via imbalance oriented selection imbalanced points. Scale assignment for imbalanced points is not straightforward because of a dilemma of involving non-maximum suppression -- The scale space theory, a popular scale assignment scheme, requests non-maximum suppression to detect extreme points from scale spaces, while imbalanced points are expected to be free of non-maximum suppression in order to maintain the localization accuracy. In this paper, we propose a bypass scheme that circumvents the above dilemma by establishing an association between an imbalanced point and a certain interest point with a known scale (e.g., key points). We justify the proposed bypass scheme theoretically and experimentally. For example, our results show that epipolar geometry estimated via imbalanced points with bypass scales is more consistent with ground truth than key points.
Keywords :
computer vision; imbalance oriented candidate selection; nonmaximum suppression; scale assignment; scale space theory; Accuracy; Detectors; Geometry; Image edge detection; Indexes; Lighting; Three dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2011 23rd IEEE International Conference on
Conference_Location :
Boca Raton, FL
ISSN :
1082-3409
Print_ISBN :
978-1-4577-2068-0
Electronic_ISBN :
1082-3409
Type :
conf
DOI :
10.1109/ICTAI.2011.37
Filename :
6103327
Link To Document :
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