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An RGB-D-Based Cross-Field of View Pose Estimation System for a Free Flight Target in a Wind Tunnel

机译:风洞中自由飞行目标的基于RGB-D的跨视场姿态估计系统

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Estimating the real-time pose of a free flight aircraft in a complex wind tunnel environment is extremely difficult. Due to the high dynamic testing environment, complicated illumination condition, and the unpredictable motion of target, most general pose estimating methods will fail. In this paper, we introduce a cross-field of view (FOV) real-time pose estimation system, which provides high precision pose estimation of the free flight aircraft in the wind tunnel environment. Multiview live RGB-D streams are used in the system as input to ensure the measurement area can be fully covered. First, a multimodal initialization method is developed to measure the spatial relationship between the RGB-D camera and the aircraft. Based on all the input multimodal information, a so-called cross-FOV model is proposed to recognize the dominating sensor and accurately extract the foreground region in an automatic manner. Second, we develop an RGB-D-based pose estimation method for a single target, by which the 3D sparse points and the pose of the target can be simultaneously obtained in real time. Many experiments have been conducted, and an RGB-D image simulation based on 3D modeling is implemented to verify the effectiveness of our algorithm. Both the real scene’s and simulation scene’s experimental results demonstrate the effectiveness of our method.
机译:在复杂的风洞环境中估算自由飞行飞机的实时姿态极为困难。由于高动态测试环境,复杂的照明条件以及目标的不可预测运动,大多数常规的姿态估计方法都将失败。在本文中,我们介绍了跨视场(FOV)实时姿态估计系统,该系统可以在风洞环境中为自由飞行飞机提供高精度的姿态估计。系统中使用多视图实时RGB-D流作为输入,以确保可以完全覆盖测量区域。首先,开发了一种多模式初始化方法来测量RGB-D相机和飞机之间的空间关系。基于所有输入的多峰信息,提出了一种所谓的交叉FOV模型,以识别主导传感器并以自动方式准确提取前景区域。其次,我们针对单个目标开发了基于RGB-D的姿态估计方法,通过该方法可以实时同时获得3D稀疏点和目标姿态。已经进行了许多实验,并基于3D建模进行了RGB-D图像仿真,以验证我们算法的有效性。真实场景和模拟场景的实验结果都证明了我们方法的有效性。

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