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» Foreground Object Detection Using Two Successive Images
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CVPR
2009
IEEE
16 years 10 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
VMV
2008
162views Visualization» more  VMV 2008»
15 years 4 months ago
Learning Distinctive Local Object Characteristics for 3D Shape Retrieval
While supervised learning approaches for 3D shape retrieval have been successfully used to incorporate human knowledge about object classes based on global shape features, the inc...
Raoul Wessel, Rafal Baranowski, Reinhard Klein
ICCV
2009
IEEE
2061views Computer Vision» more  ICCV 2009»
16 years 8 months ago
Background Subtraction for Freely Moving Cameras
Background subtraction algorithms define the background as parts of a scene that are at rest. Traditionally, these algorithms assume a stationary camera, and identify moving obj...
Yaser Sheikh, Omar Javed, Takeo Kanade
ICCV
2011
IEEE
14 years 2 months ago
The Truth about Cats and Dogs
Template-based object detectors such as the deformable parts model of Felzenszwalb et al. [11] achieve state-ofthe-art performance for a variety of object categories, but are stil...
Omkar M Parkhi, Andrea Vedaldi, C. V. Jawahar, And...
ICIP
1998
IEEE
16 years 4 months ago
EXM Eigen Templates for Detecting and Classifying Arbitrary Junctions
A novel method for extracting parametric junction and corner features in images is presented. By treating each complex feature as a combination of elementary line and edge feature...
Dibyendu Nandy, Jezekiel Ben-Arie