Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/32224
Title: A multi-scale bilateral structure tensor based corner detector
Authors: Zhang, L
Zhang, L 
Zhang, D 
Keywords: Bilateral structure tensor
Corner detector
Harris
Issue Date: 2010
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2010, v. 5995 LNCS, no. PART 2, p. 618-627 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: In this paper, a novel multi-scale nonlinear structure tensor based corner detection algorithm is proposed to improve effectively the classical Harris corner detector. By considering both the spatial and gradient distances of neighboring pixels, a nonlinear bilateral structure tensor is constructed to examine the image local pattern. It can be seen that the linear structure tensor used in the original Harris corner detector is a special case of the proposed bilateral one by considering only the spatial distance. Moreover, a multi-scale filtering scheme is developed to tell the trivial structures from true corners based on their different characteristics in multiple scales. The comparison between the proposed approach and four representative and state-of-the-art corner detectors shows that our method has much better performance in terms of both detection rate and localization accuracy.
Description: 9th Asian Conference on Computer Vision, ACCV 2009, Xi'an, 23-27 September 2009
URI: http://hdl.handle.net/10397/32224
ISBN: 3642123031
9783642123030
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-642-12304-7_58
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