首页> 外文会议>Conference on Automatic Target Recognition XIV; 20040413-20040415; Orlando,FL; US >Automatic 3D object pose estimation in IR image sequences for forward motion applications
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Automatic 3D object pose estimation in IR image sequences for forward motion applications

机译:红外图像序列中的自动3D对象姿态估计,用于前向运动应用

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The successful mission of autonomous airborne systems like unmanned aerial vehicles (UAV) strongly depends on the performance of automatic image processing used for navigation, target acquisition and terminal homing. In this paper we propose a method for automatic determination of missile position and orientation (pose) during target approach. The flight path is characterized by a forward motion, i.e. an approximately linear motion along the optical axis of the sensor system. Due to the lack of disparity, classical methods based on stereo triangulation are not suitable for 3D object recognition. To handle this we applied the SoftPOSIT algorithm, originally proposed by D. DeMenthon, and adapted it to fit our specific needs: The gathering of image points is done by multi-threshold segmentation, texture analysis, 2D tracking and edge detection. The reference points are updated in each loop and the calculated pose is smoothed using the quaternion representation of the model's orientation in order to stabilize the computations. We will show some results of image based determination of trajectories for airborne systems. Terminal homing is demonstrated by tracking the 3D pose of a vehicle in an image sequence taken in oblique view and gathered by an infrared sensor mounted to a helicopter.
机译:自主飞行系统(如无人机)的成功任务很大程度上取决于用于导航,目标获取和终端归位的自动图像处理的性能。在本文中,我们提出了一种在目标进近过程中自动确定导弹位置和方向(姿势)的方法。飞行路径的特征在于向前运动,即沿着传感器系统的光轴的近似线性运动。由于缺乏视差,基于立体三角剖分的经典方法不适用于3D对象识别。为了解决这个问题,我们应用了D. DeMenthon最初提出的SoftPOSIT算法,并对其进行了调整以适合我们的特定需求:图像点的收集是通过多阈值分割,纹理分析,2D跟踪和边缘检测完成的。每个循环中都会更新参考点,并使用模型方向的四元数表示法对计算出的姿态进行平滑处理,以稳定计算。我们将展示一些基于图像的机载系统航迹确定结果。通过以倾斜视角拍摄并由安装在直升机上的红外传感器收集的图像序列跟踪车辆的3D姿态,演示了终端归位。

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