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Projectable Classifiers for Multi-View Object Class Recognition
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
2011 (engelsk)Inngår i: 3rd International IEEE Workshop on 3D Representation and Recognition, 2011Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

We propose a multi-view object class modeling framework based on a simplified camera model and surfels (defined by a location and normal direction in a normalized 3D coordinate system) that mediate coarse correspondences between different views. Weak classifiers are learnt relative to the reference frames provided by the surfels. We describe a weak classifier that uses contour information when its corresponding surfel projects to a contour element in the image and color information when the face of the surfel is visible in the image. We emphasize that these weak classifiers can possibly take many different forms and use many different image features. Weak classifiers are combined using AdaBoost. We evaluate the method on a public dataset [8], showing promising results on categorization, recognition/detection, pose estimation and image synthesis.

sted, utgiver, år, opplag, sider
2011.
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Identifikatorer
URN: urn:nbn:se:kth:diva-49913DOI: 10.1109/ICCVW.2011.6130295ISI: 000300056700080Scopus ID: 2-s2.0-84856685061ISBN: 978-1-4673-0063-6 (tryckt)OAI: oai:DiVA.org:kth-49913DiVA, id: diva2:460615
Konferanse
3rd International IEEE Workshop on 3D Representation and Recognition (3dRR-11). Barcellona, Spain. November 07, 2011 - November 07, 2011
Merknad

QC 20111205

Tilgjengelig fra: 2011-11-30 Laget: 2011-11-30 Sist oppdatert: 2018-01-12bibliografisk kontrollert

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Totalt: 61 treff
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  • en-GB
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  • sv-SE
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