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CVPR
2007
IEEE

Virtual Training for Multi-View Object Class Recognition

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Virtual Training for Multi-View Object Class Recognition
Our goal is to circumvent one of the roadblocks to using existing approaches for single-view recognition for achieving multi-view recognition, namely, the need for sufficient training data for many viewpoints. We show how to construct virtual training examples for multi-view recognition using a simple model of objects (nearly planar facades centered at fixed 3D positions). We also show how the models can be learned from a few labeled images for each class.
Han-Pang Chiu, Leslie Pack Kaelbling, Tomás
Added 12 Oct 2009
Updated 28 Oct 2009
Type Conference
Year 2007
Where CVPR
Authors Han-Pang Chiu, Leslie Pack Kaelbling, Tomás Lozano-Pérez
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