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IJCV
1998
238views more  IJCV 1998»
15 years 8 days ago
Feature Detection with Automatic Scale Selection
The fact that objects in the world appear in different ways depending on the scale of observation has important implications if one aims at describing them. It shows that the not...
Tony Lindeberg
ISVC
2010
Springer
14 years 11 months ago
Bivariate Feature Localization for SIFT Assuming a Gaussian Feature Shape
In this paper, the well-known SIFT detector is extended with a bivariate feature localization. This is done by using function models that assume a Gaussian feature shape for the de...
Kai Cordes, Oliver Müller, Bodo Rosenhahn, J&...
AGI
2011
14 years 4 months ago
Imprecise Probability as a Linking Mechanism between Deep Learning, Symbolic Cognition and Local Feature Detection in Vision Pro
A novel approach to computer vision is outlined, involving the use of imprecise probabilities to connect a deep learning based hierarchical vision system with both local feature de...
Ben Goertzel
SMI
2010
IEEE
188views Image Analysis» more  SMI 2010»
14 years 11 months ago
Sharp Feature Detection in Point Clouds
—This paper presents a new technique for detecting sharp features on point-sampled geometry. Sharp features of different nature and possessing angles varying from obtuse to acute...
Christopher Weber, Stefanie Hahmann, Hans Hagen
92
Voted
IJCV
2008
266views more  IJCV 2008»
15 years 18 days ago
Learning to Recognize Objects with Little Supervision
This paper shows (i) improvements over state-of-the-art local feature recognition systems, (ii) how to formulate principled models for automatic local feature selection in object c...
Peter Carbonetto, Gyuri Dorkó, Cordelia Sch...