Proceedings of the 25th annual conference on Computer graphics and interactive techniques
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Acquiring a Radiance Distribution to Superimpose Virtual Objects onto a Real Scene
IEEE Transactions on Visualization and Computer Graphics
Exact Two-Image Structure from Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Creating Image-Based VR Using a Self-Calibrating Fisheye Lens
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Omnidirectional camera model and epipolar geometry estimation by RANSAC with bucketing
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Estimation of omnidirectional camera model from epipolar geometry
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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This paper presents a new self-calibration algorithm of omnidirectional camera from uncalibrated images by considering the inlier distribution. First, one parametric non-linear projection model of omnidirectional camera is estimated with the known rotation and translation parameters. After deriving projection model, we can compute an essential matrix of the camera with unknown motions, and then determine the camera positions. The standard deviations are used as a quantitative measure to select a proper inlier set. The experimental results showed that we can achieve a precise estimation of the omnidirectional camera model and extrinsic parameters including rotation and translation.