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

M. Odelga, N. Kochanek, H. Bülthoff
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引用次数: 12

Abstract

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.
仅使用IMU数据的无人机高效实时视频稳定
虽然一些无人驾驶飞行器(uav)有能力携带机械稳定的摄像设备,但重量限制或其他问题可能使机械稳定不切实际。因此,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,由于多旋翼的风和加速度运动,视频流往往是不稳定的。这些视频流通常由人类和机器进行分析,而不必要的摄像机移动可能会给两者都带来问题。对于人类观察者来说,不必要的运动可能只是让他们更难跟上视频,而对于计算机算法来说,它可能会严重损害算法的预期功能。关于如何使用特征跟踪来确定摄像机的运动来稳定视频,这反过来又用于操纵帧和稳定摄像机流,已经有了大量的研究。然而,我们相信,通过使用无人机机载惯性测量单元(IMU)的数据来稳定相机馈送,这一过程可以大大简化。本文提出了一种仅基于无人机平台IMU数据的视频稳像算法。我们的结果表明,我们的算法成功地稳定了相机流,并且需要更少的计算能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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