首页> 外文会议>International Joint Conference on Computer Vision and Computer Graphics Theory and Applications >AUTONOMOUS MODEL-BASED OBJECT IDENTIFICATION CAMERA POSITION ESTIMATION WITH APPLICATION TO AIRPORT LIGHTING QUALITY CONTROL
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AUTONOMOUS MODEL-BASED OBJECT IDENTIFICATION CAMERA POSITION ESTIMATION WITH APPLICATION TO AIRPORT LIGHTING QUALITY CONTROL

机译:基于自主模型的对象识别和相机位置估计,应用于机场照明质量控制

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The development of an autonomous system for the accurate measurement of the quality of aerodrome ground lighting (AGL) in accordance with current standards and recommendations is presented. The system is composed of an imager which is placed inside the cockpit of an aircraft to record images of the AGL during a normal descent to an aerodrome. Before the performance of the AGL is assessed, it is first necessary to uniquely identify each luminaire within the image and track it through the complete image sequence. A model-based (MB) methodology is used to ascertain the optimum match between a template of the AGL and the actual image data. Projective geometry, in addition to the image and real world location of the extracted luminaires, is then used to calculate the position of the camera at the instant the image was acquired. Algorithms are also presented which model the distortion apparent within the sensors optical system and average the camera's intrinsic parameters over multiple frames, so as to minimise the effects of noise on the acquired image data and hence make the camera's estimated position and orientation more accurate. The positional information is validated using actual approach image data.
机译:提出了一种自治系统,用于准确测量根据当前标准和建议的机场接地照明(AGL)的质量。该系统由成像仪组成,该成像器被放置在飞机的驾驶舱内,以在正常下降到机场期间记录AGL的图像。在评估AGL性能之前,首先需要唯一地识别图像内的每个灯具并通过完整的图像序列跟踪它。基于模型的(MB)方法用于确定AGL和实际图像数据模板之间的最佳匹配。然后,除了提取的灯具的图像和现实世界位置之外,还将用于计算图像被获取的瞬间的相机的位置。还提出了算法,该算法模型在传感器光学系统内的变形和在多个帧上平均相机的内在参数,以最小化噪声对所获取的图像数据的影响,因此使得相机的估计位置和方向更准确。使用实际接种图像数据验证位置信息。

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