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» Randomness and Geometric Features in Computer Vision
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JMLR
2008
168views more  JMLR 2008»
13 years 7 months ago
Max-margin Classification of Data with Absent Features
We consider the problem of learning classifiers in structured domains, where some objects have a subset of features that are inherently absent due to complex relationships between...
Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbe...
ICPR
2006
IEEE
14 years 8 months ago
Radon space and Adaboost for Pose Estimation
In this paper, we present a new approach to camera pose estimation from single shot images in known environment. Such a method comprises two stages, a learning step and an inferen...
Patrick Etyngier, Nikos Paragios, Renaud Keriven, ...
ECCV
2010
Springer
13 years 8 months ago
Semantic Segmentation of Urban Scenes Using Dense Depth Maps
In this paper we present a framework for semantic scene parsing and object recognition based on dense depth maps. Five viewindependent 3D features that vary with object class are e...
Chenxi Zhang, Liang Wang, Ruigang Yang
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 9 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
ICCV
2009
IEEE
15 years 18 days ago
Optimal Correspondences from Pairwise Constraints
Correspondence problems are of great importance in computer vision. They appear as subtasks in many applications such as object recognition, merging partial 3D reconstructions a...
Olof Enqvist, Klas Josephson, Fredrik Kahl