Article ID Journal Published Year Pages File Type
4968703 Computer Vision and Image Understanding 2017 23 Pages PDF
Abstract
360° and spherical cameras become popular and are convenient for applications like immersive videos. They are often built by fixing together several fisheye cameras pointing in different directions. However their complete self-calibration is not easy since the consumer fisheyes are rolling shutter cameras which can be unsynchronized. Our approach does not require a calibration pattern. First the multi-camera model is initialized thanks to assumptions that are suitable to an omnidirectional camera without a privileged direction: the cameras have the same setting and are roughly equiangular. Second a frame-accurate synchronization is estimated from the instantaneous angular velocities of each camera provided by monocular structure-from-motion. Third both inter-camera poses and intrinsic parameters are refined using multi-camera structure-from-motion and bundle adjustment. Last we introduce a bundle adjustment that estimates not only the usual parameters but also a sub-frame-accurate synchronization and the rolling shutter. We experiment using videos taken by consumer cameras mounted on a helmet and moving along trajectories of several hundreds of meters or kilometers, and compare our results to ground truth.
Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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