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

机译:UAV使用Fisheye镜头相机和平移/倾斜摄像机的多级贝叶斯目标估算

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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:本文介绍了一种无人驾驶飞行器的广义多级贝叶斯方法,以估计移动目标的位置。所提出的方法的主要硬件组件是具有鱼眼镜镜头的相机和具有正常镜头和平移/倾斜单元的另一相机。具有广视角(AOV),鱼眼镜头相机首先检测目标的轴承,PT相机接下来捕获其AOV中的目标。递归贝叶斯估计稳定地将目标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级检测方法。置信度与每个检测技术的检测概率(POD)结合定义,并且Fisheye透镜通过逐渐增加吊舱而能够连续检测。观察可能性最终以广义的方式从豆荚衍生。通过多转子直升机对所提出的方法应用于检测移动目标,结果表明了所提出的多级贝叶斯方法和多阶段鱼眼镜头检测方法的有效性。

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