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85
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ECCV
1996
Springer
16 years 15 hour 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
84
Voted
IJCV
2000
149views more  IJCV 2000»
14 years 10 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
95
Voted
VMV
2001
209views Visualization» more  VMV 2001»
14 years 11 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
80
Voted
ICPR
2004
IEEE
15 years 11 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»
14 years 10 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