Feature detection with an improved anisotropic filter.
Date
2006
Authors
Gobara, M.
Suter, D.
Editors
Narayanan, P.J.
Nayar, S.K.
Shum, H.Y.
Nayar, S.K.
Shum, H.Y.
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Conference paper
Citation
Computer Vision – ACCV 2006: 7th Asian Conference on Computer Vision Hyderabad, India, January 13-16, 2006, Proceedings, Part II / P.J. Narayanan, Shree K. Nayar, Heung-Yeung Shum (eds.), pp.643-652
Statement of Responsibility
Mohamed Gobara and David Suter
Conference Name
Asian Conference on Computer Vision (7th : 2006 : Hyderabad, India)
Abstract
The problem of detecting local image features that are invariant to scale, orientation, illumination and viewpoint changes is a critical issue in many computer vision applications. The challenges involve localizing the image features accurately in the spatial and frequency domains and describing them with a stable analytical representation. In this paper we address these two issues by proposing a new non-linear scale-space implementation that improves the localization accuracy of the SIFT [3] local features. Furthermore we propose a simple adjustment to the standard SIFT descriptor and show that the modified version is more robust to affine changes.
School/Discipline
Dissertation Note
Provenance
Description
© Springer-Verlag Berlin Heidelberg 2006