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» Comparison of invariant descriptors for object recognition
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ICCV
2005
IEEE
14 years 9 months ago
Local Features for Object Class Recognition
In this paper we compare the performance of local detectors and descriptors in the context of object class recognition. Recently, many detectors / descriptors have been evaluated ...
Krystian Mikolajczyk, Bastian Leibe, Bernt Schiele
ICANN
2007
Springer
14 years 1 months ago
A Comparison of Features in Parts-Based Object Recognition Hierarchies
Parts-based recognition has been suggested for generalizing from few training views in categorization scenarios. In this paper we present the results of a comparative investigation...
Stephan Hasler, Heiko Wersing, Edgar Körner
ACCV
2006
Springer
14 years 1 months ago
Biologically Motivated Perceptual Feature: Generalized Robust Invariant Feature
Abstract. In this paper, we present a new, biologically inspired perceptual feature to solve the selectivity and invariance issue in object recognition. Based on the recent findin...
Sungho Kim, In-So Kweon
BCS
2008
13 years 9 months ago
Improved SIFT-Features Matching for Object Recognition
: The SIFT algorithm (Scale Invariant Feature Transform) proposed by Lowe [1] is an approach for extracting distinctive invariant features from images. It has been successfully app...
Faraj Alhwarin, Chao Wang, Danijela Ristic-Durrant...
ICPR
2008
IEEE
14 years 2 months ago
Illumination invariant spatio-colorimetric normalization
In the context of object recognition, it is useful to extract, from the images, efficient indexes that are insensitive to the illumination conditions, to the camera scale factor ...
Damien Muselet, Alain Trémeau