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» Learning Models for Object Recognition
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156
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CVPR
2012
IEEE
13 years 6 months ago
From Pictorial Structures to deformable structures
Pictorial Structures (PS) define a probabilistic model of 2D articulated objects in images. Typical PS models assume an object can be represented by a set of rigid parts connecte...
Silvia Zuffi, Oren Freifeld, Michael J. Black
140
Voted
KDD
2004
ACM
210views Data Mining» more  KDD 2004»
16 years 4 months ago
Web usage mining based on probabilistic latent semantic analysis
The primary goal of Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of user sessions and discoveri...
Xin Jin, Yanzan Zhou, Bamshad Mobasher
127
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PAMI
2002
112views more  PAMI 2002»
15 years 3 months ago
Feature Space Trajectory Methods for Active Computer Vision
We advance new active object recognition algorithms that classify rigid objects and estimate their pose from intensity images. Our algorithms automatically detect if the class or p...
Michael A. Sipe, David Casasent
ICOST
2011
Springer
14 years 7 months ago
Using Association Rule Mining to Discover Temporal Relations of Daily Activities
The increasing aging population has inspired many machine learning researchers to find innovative solutions for assisted living. A problem often encountered in assisted living set...
Ehsan Nazerfard, Parisa Rashidi, Diane J. Cook
ICCV
2001
IEEE
16 years 5 months ago
Topology Free Hidden Markov Models: Application to Background Modeling
Hidden Markov Models (HMMs) are increasingly being used in computer vision for applications such as: gesture analysis, action recognition from video, and illumination modeling. Th...
Bjoern Stenger, Visvanathan Ramesh, Nikos Paragios...