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|Title:||Feature detection with an improved anisotropic filter.|
|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|
|Series/Report no.:||Lecture Notes in Computer Science, 2006; 3852: 643-652|
|Conference Name:||Asian Conference on Computer Vision (7th : 2006 : Hyderabad, India)|
|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  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|
|Appears in Collections:||Aurora harvest|
Computer Science publications
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