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Self-calibration of omnidirectional multi-cameras including synchronization and rolling shutter

机译:全方位同步摄像机的自校准,包括同步和卷帘快门

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摘要

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.
机译:360°和球形摄像机变得越来越流行,并且对于沉浸式视频等应用非常方便。它们通常是通过将指向不同方向的多个鱼眼摄像机固定在一起而构建的。然而,由于消费者的鱼眼镜头是可能不同步的卷帘式相机,因此要进行完整的自校准并不容易。我们的方法不需要校准模式。首先,由于适用于无特权方向的全向摄像机的假设而初始化了多摄像机模型:摄像机具有相同的设置并且大致等角。其次,从单眼运动结构提供的每个摄像机的瞬时角速度估计帧精确的同步。第三,使用从运动和束调整的多摄像机结构来完善摄像机之间的姿势和固有参数。最后,我们介绍了一种束调整,该束调整不仅可以估算通常的参数,而且还可以估算子帧精确的同步和滚动快门。我们使用安装在头盔上的消费者照相机拍摄的视频进行实验,这些视频沿着数百米或几千米的轨迹移动,并将我们的结果与真实情况进行比较。

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