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2017
Conference Paper
Title
Efficient pose selection for interactive camera calibration
Abstract
The choice of poses for camera calibration with planar patterns is only rarely considered - yet the calibration precision heavily depend on it. This work presents a pose selection method that explicitly avoids singular pose configurations which would lead to an unreliable solution. Consequently camera poses are favoured that reduce the uncertainty of the calibration parameters most. For this purpose the quality of the calibration parameters is continuously estimated using uncertainty propagation. Our approach performs better than comparable solutions while requiring 30% less calibration frames.
Keyword(s)
artificial intelligence (AI)
Vision understanding
scene understanding
modeling of physical attributes
recovery of physical attribute
pattern recognition
implementation
interactive system
Lead Topic: Digitized Work
Lead Topic: Individual Health
Lead Topic: Smart City
Lead Topic: Visual Computing as a Service
Research Line: Computer vision (CV)
Research Line: Human computer interaction (HCI)