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CVPR
2007
IEEE
14 years 9 months ago
Learning the Compositional Nature of Visual Objects
The compositional nature of visual objects significantly limits their representation complexity and renders learning of structured object models tractable. Adopting this modeling ...
Björn Ommer, Joachim M. Buhmann
CVPR
2010
IEEE
14 years 4 months ago
Learning a Hierarchy of Discriminative Space-Time Neighborhood Features for Human Action Recognition
Recent work shows how to use local spatio-temporal features to learn models of realistic human actions from video. However, existing methods typically rely on a predefined spatial...
Adriana Kovashka, Kristen Grauman
VISAPP
2007
13 years 8 months ago
Extraction of multi-modal object representations in a robot vision system
We introduce one module in a cognitive system that learns the shape of objects by active exploration. More specifically, we propose a feature tracking scheme that makes use of the...
Nicolas Pugeault, Emre Baseski, Dirk Kraft, Floren...
CVPR
2012
IEEE
11 years 10 months ago
3D landmark model discovery from a registered set of organic shapes
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to repla...
Clement Creusot, Nick Pears, Jim Austin
CVPR
2004
IEEE
14 years 9 months ago
Flexible Spatial Models for Grouping Local Image Features
A key step for the effective use of local image features (i.e., highly distinctive and robust features) for recognition or image matching is the appropriate grouping of feature ma...
Gustavo Carneiro, Allan D. Jepson