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Accurate estimation of object location in an image sequence using helicopter flight data

机译:使用直升机飞行数据准确估计图像序列中的对象位置

摘要

In autonomous navigation, it is essential to obtain a three-dimensional (3D) description of the static environment in which the vehicle is traveling. For a rotorcraft conducting low-latitude flight, this description is particularly useful for obstacle detection and avoidance. In this paper, we address the problem of 3D position estimation for static objects from a monocular sequence of images captured from a low-latitude flying helicopter. Since the environment is static, it is well known that the optical flow in the image will produce a radiating pattern from the focus of expansion. We propose a motion analysis system which utilizes the epipolar constraint to accurately estimate 3D positions of scene objects in a real world image sequence taken from a low-altitude flying helicopter. Results show that this approach gives good estimates of object positions near the rotorcraft's intended flight-path.
机译:在自主导航中,获取车辆行驶的静态环境的三维(3D)描述至关重要。对于进行低纬度飞行的旋翼飞机,此描述对于障碍物的检测和避开特别有用。在本文中,我们从低纬度直升机拍摄的单眼图像序列中解决了静态物体的3D位置估计问题。由于环境是静态的,因此众所周知,图像中的光流将从扩展的焦点产生辐射图。我们提出了一种运动分析系统,该系统利用对极约束来准确估计从低空飞行直升机拍摄的真实世界图像序列中场景对象的3D位置。结果表明,这种方法可以很好地估计旋翼飞机预期飞行路径附近的物体位置。

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