Generic self-calibration of central cameras
Computer Vision and Image Understanding
Camera Models and Fundamental Concepts Used in Geometric Computer Vision
Foundations and Trends® in Computer Graphics and Vision
On the global self-calibration of central cameras using two infinitesimal rotations
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
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The paper proposes a novel approach for planar self-calibration of radially symmetric cameras. We model these camera images using notions of distortion center and concentric distortion circles around it. The rays corresponding to pixels lying on a single distortion circle form a right circular cone. Each of these cones is associated with two unknowns; optical center and focal length (opening angle). In the central case, we consider all distortion circles to have the same optical center, whereas in the non-central case they have different optical centers lying on the same optical axis. Based on this model we provide a factorization based self-calibration algorithm for planar scenes from dense image matches. Our formulation provides a rich set of constraints to validate the correctness of the distortion center. We also propose possible extensions of this algorithm in terms of non-planar scenes, non-unit aspect ratio and multi-view constraints. Experimental results are shown.