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

Sheng Liu, Yuan Feng, Kang Shen, Yangqing Wang and Shengyong Chen

Complexity, 2018, vol. 2018, 1-9

Abstract:

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.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:7358491

DOI: 10.1155/2018/7358491

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