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Moving object detection, tracking and following using an omnidirectional camera on a mobile robot

机译:使用移动机器人上的全向摄像机进行运动对象检测,跟踪和跟踪

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Equipping mobile robots with an omnidirectional camera is very advantageous in numerous applications as all information about the surrounding scene is stored in a single image frame. In the given context, the present paper is concerned with detection, tracking and following of a moving object with an omnidirectional camera. The camera calibration and image formation is based on the spherical unified projection model thus yielding a representation of the omnidirectional image on the unit sphere. Detection of moving objects is performed by calculating a sparse optical flow in the image and then lifting the flow vectors on the unit sphere where they are discriminated as dynamic or static by analytically calculating the distance of the terminal vector point to a great circle arc. The flow vectors are then clustered and the center of gravity is calculated to form the sensor measurement. Furthermore, the tracking is posed as a Bayesian estimation problem on the unit sphere and the solution based on the von Mises-Fisher distribution is utilized. Visual servoing is performed for the object following task where the control law calculation is based on the projection of a point on the unit sphere. Experimental results obtained by a camera with a fish-eye lens mounted on a differential drive mobile robot are presented and discussed.
机译:在众多应用中,为移动机器人配备全向摄像机非常有利,因为有关周围场景的所有信息都存储在单个图像帧中。在给定的背景下,本文涉及利用全向摄像机对运动物体的检测,跟踪和跟踪。相机校准和图像形成基于球形统一投影模型,因此可以在单位球面上产生全向图像的表示。通过计算图像中的稀疏光流,然后通过分析计算最终矢量点到大圆弧的距离,将流矢量提升为动态或静态,将运动矢量提升到单位球体上,从而进行运动对象的检测。然后将流向量聚类,并计算重心以形成传感器测量值。此外,在单位球面上将跟踪作为贝叶斯估计问题提出,并利用基于冯·米塞斯·费舍尔分布的解。对目标跟随任务执行视觉伺服,其中控制律的计算基于点在单位球面上的投影。提出并讨论了通过将鱼眼镜头安装在差动驱动移动机器人上的摄像机获得的实验结果。

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