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» Visual Object Recognition Through One-Class Learning
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ICPR
2008
IEEE
15 years 6 months ago
Ranking the local invariant features for the robust visual saliencies
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and ...
Shengping Xia, Peng Ren, Edwin R. Hancock
136
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TIP
2008
344views more  TIP 2008»
14 years 11 months ago
A Self-Organizing Approach to Background Subtraction for Visual Surveillance Applications
Detection of moving objects in video streams is the first relevant step of information extraction in many computer vision applications. Aside from the intrinsic usefulness of being...
Lucia Maddalena, Alfredo Petrosino
JMLR
2010
192views more  JMLR 2010»
14 years 6 months ago
Efficient Learning of Deep Boltzmann Machines
We present a new approximate inference algorithm for Deep Boltzmann Machines (DBM's), a generative model with many layers of hidden variables. The algorithm learns a separate...
Ruslan Salakhutdinov, Hugo Larochelle
CVPR
2009
IEEE
16 years 6 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese
ICRA
2008
IEEE
134views Robotics» more  ICRA 2008»
15 years 6 months ago
Towards robust place recognition for robot localization
— Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of hi...
Muhammad Muneeb Ullah, Andrzej Pronobis, Barbara C...