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ECCV
1996
Springer
14 years 6 months ago
Object Recognition Using Multidimensional Receptive Field Histograms
This paper presents a technique to determine the identity of objects in a scene using histograms of the responses of a vector of local linear neighborhood operators (receptive elds...
Bernt Schiele, James L. Crowley
IJCV
2000
149views more  IJCV 2000»
13 years 4 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
VMV
2001
209views Visualization» more  VMV 2001»
13 years 6 months ago
A Novel Probabilistic Model for 3D Object Recognition: Spin-Glass Markov Random Fields
This contribution presents a new class of MRF, that is inspired by methods of statistical physics. The new energy function assumes full-connectivity in the neighborhood system and...
Barbara Caputo, Sahla Bouattour, Dietrich Paulus
ICPR
2004
IEEE
14 years 5 months ago
Object Recognition Using Composed Receptive Field Histograms of Higher Dimensionality
Recent work has shown that effective methods for recognising objects or spatio-temporal events can be constructed based on receptive field responses summarised into histograms or ...
Oskar Linde, Tony Lindeberg
IJCV
2008
241views more  IJCV 2008»
13 years 4 months ago
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Jim Mutch, David G. Lowe