Adelaide Research & Scholarship
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https://hdl.handle.net/2440/56252
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| Type: | Conference paper |
| Title: | Feature detection with an improved anisotropic filter. |
| Author: | Gobara, M. Suter, D. |
| 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 |
| Publisher: | Springer |
| Publisher Place: | Berlin |
| Issue Date: | 2006 |
| Series/Report no.: | Lecture Notes in Computer Science, 2006; 3852: 643-652 |
| ISBN: | 3-540-31244-7 9783540312444 |
| ISSN: | 0302-9743 1611-3349 |
| Conference Name: | Asian Conference on Computer Vision (7th : 2006 : Hyderabad, India) |
| Editor: | Narayanan, P.J. Nayar, S.K. Shum, H.Y. |
| Statement of Responsibility: | Mohamed Gobara and David Suter |
| 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. |
| Description: | © Springer-Verlag Berlin Heidelberg 2006 |
| DOI: | 10.1007/11612704_64 |
| Appears in Collections: | Aurora harvest Computer Science publications |
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