A Unified Theory of Uncalibrated Stereo for Both Perspective and Affine Cameras
Journal of Mathematical Imaging and Vision
Practical Structure and Motion from Stereo When Motion is Unconstrained
International Journal of Computer Vision
Bundle Adjustment - A Modern Synthesis
ICCV '99 Proceedings of the International Workshop on Vision Algorithms: Theory and Practice
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Visual Navigation of Uncalibrated Mobile Robots from Uncalibrated Stereo Pointers
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Edge-preserving Simultaneous Joint Motion-Disparity Estimation
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
Virtual View Synthesis from Uncalibrated Stereo Cameras
ICMCS '99 Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02
Continuous stereo self-calibration by camera parameter tracking
IEEE Transactions on Image Processing
On 3-D scene flow and structure recovery from multiview image sequences
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Parallel tracking and mapping with multiple cameras on an unmanned aerial vehicle
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
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The recent resurgence of stereoscopic 3D films has triggered a high demand for post-processing tools for stereoscopic image sequences. Camera motion estimation, also known as structure-from-motion (SfM) or match-moving, is an essential step in the post-processing pipeline. In order to ensure a high accuracy of the estimated camera parameters, a bundle adjustment algorithm should be employed. We present a new stereo camera model for bundle adjustment. It is designed to be applicable to a wide range of cameras employed in today's movie productions. In addition, we describe how the model can be integrated efficiently into the sparse bundle adjustment framework, enabling the processing of stereoscopic image sequences with traditional efficiency and improved accuracy. Our camera model is validated by synthetic experiments, on rendered sequences, and on a variety of real-world video sequences.