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WACV
2005
IEEE
15 years 3 months ago
Incorporating Background Invariance into Feature-Based Object Recognition
Current feature-based object recognition methods use information derived from local image patches. For robustness, features are engineered for invariance to various transformation...
Andrew N. Stein, Martial Hebert
IJCV
2000
149views more  IJCV 2000»
14 years 9 months ago
Recognition without Correspondence using Multidimensional Receptive Field Histograms
The appearance of an object is composed of local structure. This local structure can be described and characterized by a vector of local features measured by local operators such a...
Bernt Schiele, James L. Crowley
ICIAP
2007
ACM
15 years 10 months ago
A Method for Blur and Similarity Transform Invariant Object Recognition
In this paper, we propose novel blur and similarity transform (i.e. rotation, scaling and translation) invariant features for the recognition of objects in images. The features ar...
Janne Heikkilä, Ville Ojansivu
ICRA
2010
IEEE
107views Robotics» more  ICRA 2010»
14 years 8 months ago
Using stereo for object recognition
— There has been significant progress recently in object recognition research, but many of the current approaches still fail for object classes with few distinctive features, an...
Scott Helmer, David G. Lowe
SPIESR
2000
104views Database» more  SPIESR 2000»
14 years 11 months ago
Feature localization and search by object model under illumination change
Color object recognition methods that are based on image retrieval algorithms can handle changes of illumination via image normalization, e.g. simple color-channel-normalization1 ...
Mark S. Drew, Zinovi Tauber, Ze-Nian Li