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Multi-stage Bayesian target estimation by UAV using fisheye lens camera and pan/tilt camera

机译:使用鱼眼镜头相机和云台相机的无人机多阶段贝叶斯目标估计

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This paper presents a generalized multi-stage Bayesian approach for an unmanned aerial vehicle to estimate the location of a mobile target. The major hardware components of the proposed approach are a camera with a fisheye lens and another camera with a normal lens and a pan/tilt unit. With wide angle of view (AOV), the fisheye lens camera first detects the bearing of the target, and the PT camera next captures the target in its AOV. The recursive Bayesian estimation steadily locates the target in a globally defined space. The paper also proposes a multi-stage detection method for the fisheye lens camera. The level of confidence is defined in association with the probability of detection (POD) for each detection technique, and the fisheye lens enables continuous detection by gradually increasing the POD. The observation likelihood is finally derived from the POD in a generalized manner. The proposed approach was applied to the detection of a mobile target by a multi-rotor helicopter, and results have demonstrated the effectiveness of both the proposed multi-stage Bayesian approach and multi-stage fisheye lens detection method.
机译:本文提出了一种用于无人机的通用多阶段贝叶斯方法,以估计可移动目标的位置。所提出的方法的主要硬件组件是带有鱼眼镜头的摄像机,以及带有普通透镜和云台的摄像机。鱼眼镜头相机具有广视角(AOV),首先检测目标物的方位,然后PT相机在其AOV中捕获目标物。递归贝叶斯估计将目标稳定地定位在全局定义的空间中。本文还提出了一种用于鱼眼镜头相机的多阶段检测方法。与每种检测技术的检测概率(POD)相关联地定义置信度,并且鱼眼镜头通过逐渐增加POD来实现连续检测。观察可能性最终以广义方式从POD中得出。将该方法应用于多旋翼直升机对可移动目标的检测,结果证明了所提出的多级贝叶斯方法和多级鱼眼镜头检测方法的有效性。

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