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TIP
2002
179views more  TIP 2002»
13 years 7 months ago
Unsupervised image classification, segmentation, and enhancement using ICA mixture models
An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of i...
Te-Won Lee, Michael S. Lewicki
BMVC
2010
13 years 5 months ago
Improving object classification using semantic attributes
This paper shows how semantic attribute features can be used to improve object classification performance. The semantic attributes used fall into five groups: scene (e.g. `road�...
Yu Su, Moray Allan, Frédéric Jurie
ICMLA
2009
13 years 5 months ago
Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Johannes Hartz
CVPR
2008
IEEE
14 years 9 months ago
Selective hidden random fields: Exploiting domain-specific saliency for event classification
Classifying an event captured in an image is useful for understanding the contents of the image. The captured event provides context to refine models for the presence and appearan...
Vidit Jain, Amit Singhal, Jiebo Luo
ACIVS
2007
Springer
13 years 11 months ago
Patch-Based Experiments with Object Classification in Video Surveillance
We present a patch-based algorithm for the purpose of object classification in video surveillance. Within detected regions-of-interest (ROIs) of moving objects in the scene, a feat...
Rob G. J. Wijnhoven, Peter H. N. de With