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» Statistical Models of Appearance for Computer Vision
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CVPR
2008
IEEE
16 years 1 months ago
Object categorization using co-occurrence, location and appearance
In this work we introduce a novel approach to object categorization that incorporates two types of context ? cooccurrence and relative location ? with local appearancebased featur...
Carolina Galleguillos, Andrew Rabinovich, Serge Be...
CVPR
2010
IEEE
15 years 5 months ago
Learning Appearance in Virtual Scenarios for Pedestrian Detection
Detecting pedestrians in images is a key functionality to avoid vehicle-to-pedestrian collisions. The most promising detectors rely on appearance-based pedestrian classifiers tra...
Francisco Marin Tur, David Vazquez, David Geronimo...
ECCV
2002
Springer
16 years 1 months ago
Probabalistic Models and Informative Subspaces for Audiovisual Correspondence
Abstract. We propose a probabalistic model of single source multimodal generation and show how algorithms for maximizing mutual information can find the correspondences between com...
John W. Fisher III, Trevor Darrell
CVPR
2000
IEEE
16 years 1 months ago
A General Method for Errors-in-Variables Problems in Computer Vision
The Errors-in-Variables (EIV) model from statistics is often employed in computer vision thoughonlyrarely under this name. In an EIV model all the measurements are corrupted by no...
Bogdan Matei, Peter Meer
WACV
2005
IEEE
15 years 5 months ago
Shared Features for Scalable Appearance-Based Object Recognition
We present a framework for learning object representations for fast recognition of a large number of different objects. Rather than learning and storing feature representations s...
Erik Murphy-Chutorian, Jochen Triesch