The paper presents a method to solve this problem using canonical sets of scale space features. Qualitative and quantitative analysis show improved performance ...
The paper presents a method to solve this problem using canonical sets of scale space features. Qualitative and quantitative analysis show improved performance ...
May 30, 2007 · The paper presents a method to solve this problem using canonical sets of scale space features. Qualitative and quantitative analysis show ...
The paper presents a method to solve this problem using canonical sets of scale space features. Qualitative and quantitative analysis show improved performance ...
In order to investigate the deep structure of Gaussian scale space images, one needs to understand the behaviour of critical points under the influence of ...
... Scale-Space Trees -- Generic Maximum Likely Scale Selection -- Combining Different Types of Scale Space Interest Points Using Canonical Sets -- Feature ...
In this paper we will consider the problem of combining multiple types of interest points used for image reconstruction. It is shown that ordering the complete ...
Affine covariant interest points can in turn be obtained by combining any of these three interest point operators with subsequent affine shape adaptation ...
These points are defined by: ... Combining Different Types of Scale Space Interest Points Using Canonical Sets. Conference Paper. Full-text available. May 2007.
Scale-space theory is a framework for multi-scale signal representation developed by the computer vision, image processing and signal processing communities