Using Spatially Distributed Patterns for Multiple View Camera Calibration
This paper presents an approach to intrinsic and extrinsic camera parameter calibration from a series of photographs or from video. For the reliable and accurate estimation of camera parameters it is common to use specially designed calibration patterns. However, using a single pattern, a globally consistent calibration is only possible from positions and viewing directions from where this single pattern is visible. To overcome this problem, the presented approach uses multiple coded patterns that can be distributed over a large area. A connection graph representing visible patterns in multiple views is generated, which is used to estimate globally consistent camera parameters for the complete scene. The approach is evaluated on synthetic and real-world ground truth examples. Furthermore, the approach is applied to calibrate the stereo-cameras of a robotic head on a moving platform.
KeywordsAugmented Reality Camera Calibration View Camera Camera Parameter Bundle Adjustment
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