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Efficient real-time video stabilization for UAVs using only IMU data

机译:仅使用IMU数据的UAV的高效实时视频稳定化

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While some unmanned aerial vehicles (UAVs) have the capacity to carry mechanically stabilized camera equipment, weight limits or other problems may make mechanical stabilization impractical. As a result many UAVs rely on fixed cameras to provide a video stream to an operator or observer. With a fixed camera, the video stream is often unsteady due to the multirotor's movement from wind and acceleration. These video streams are often analyzed by both humans and machines, and the unwanted camera movement can cause problems for both. For a human observer, unwanted movement may simply make it harder to follow the video, while for computer algorithms, it may severely impair the algorithm's intended function. There has been significant research on how to stabilize videos using feature tracking to determine camera movement, which in turn is used to manipulate frames and stabilize the camera stream. We believe, however, that this process could be greatly simplified by using data from a UAV's on-board inertial measurement unit (IMU) to stabilize the camera feed. In this paper we present an algorithm for video stabilization based only on IMU data from a UAV platform. Our results show that our algorithm successfully stabilizes the camera stream with the added benefit of requiring less computational power.
机译:尽管某些无人驾驶飞机(UAV)具有携带机械稳定的摄像设备的能力,但是重量限制或其他问题可能使机械稳定变得不切实际。结果,许多无人机依靠固定摄像机向操作员或观察者提供视频流。在固定摄像机的情况下,由于多旋翼由于风和加速度而运动,因此视频流通常不稳定。这些视频流通常由人和机器进行分析,不必要的摄像机移动可能会给两者带来麻烦。对于人类观察者而言,不必要的移动可能只会使跟随视频变得更加困难,而对于计算机算法而言,可能会严重损害算法的预期功能。对于如何使用特征跟踪来确定摄像机的运动来稳定视频,已有大量研究,反过来又用于操纵帧并稳定摄像机流。但是,我们认为,通过使用来自无人机的机载惯性测量单元(IMU)的数据来稳定摄像机的馈送,可以大大简化此过程。在本文中,我们提出了一种仅基于来自UAV平台的IMU数据进行视频稳定的算法。我们的结果表明,我们的算法成功地稳定了摄像机流,并具有所需的较少计算能力的额外好处。

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