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Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Hinterstoisser, S.; Benhimane, S.; Navab, N.; Fua, P.; Lepetit, V.
Titel:
Online Learning of Patch Perspective Rectification for Efficient Object Detection
Abstract:
For a large class of applications, there is time to train the system. In this paper, we propose a learning-based approach to patch perspective rectification, and show that it is both faster and more reliable than state-of-the-art ad hoc affine region detection methods. Our method performs in three steps. First, a classifier provides for every keypoint not only its identity, but also a first estimate of its transformation. This estimate allows carrying out, in the second step, an accurate...     »
Stichworte:
CAMP,VisionCAD,CAMPComputerVision,ComputerVision,CVPR
Jahr:
2008
Hinweise:
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