APPARATUS AND METHOD FOR INFERENCING TOPOLOGY OF MULTIPLE CAMERAS NETWORK BY TRACKING MOVEMENT
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    发明申请
    APPARATUS AND METHOD FOR INFERENCING TOPOLOGY OF MULTIPLE CAMERAS NETWORK BY TRACKING MOVEMENT 有权
    用于通过跟踪运动来感染多个摄像机网络拓扑的装置和方法

    公开(公告)号:US20100231723A1

    公开(公告)日:2010-09-16

    申请号:US12675682

    申请日:2007-10-23

    IPC分类号: H04N5/225 G06K9/00

    摘要: Provided are an apparatus and a method for tracking movements of objects to infer a topology of a network of multiple cameras. The apparatus infers the topology of the network formed of the multiple cameras that sequentially obtain images and includes an object extractor, a haunting data generator, and a haunting database (DB), and a topology inferrer. The object extractor extracts at least one from each of the obtained images, for the multiple cameras. The haunting data generator generates appearing cameras and appearing times at which the moving objects appear, and disappearing cameras and disappearing times at which the moving objects disappear, for the multiple cameras. The haunting DB stores the appearing cameras and appearing times and the disappearing cameras and disappearing times of the moving object, for the multiple cameras. The topology inferrer infers the topology of the network using the appearing cameras and appearing times and the disappearing cameras and disappearing times of moving objects. Therefore, the apparatus accurately infers topologies and distances among the multiple cameras in the network of the multiple cameras using the cameras and appearing and disappearing times at which the moving objects appear and disappear. As a result, the apparatus accurately track the moving objects in the network.

    摘要翻译: 提供了一种用于跟踪对象的移动以推断多个摄像机的网络的拓扑的装置和方法。 该装置推断由顺序获得图像的多个摄像机形成的网络的拓扑结构,并且包括对象提取器,困扰数据生成器和困扰数据库(DB)以及拓扑推断器。 对于多个摄像机,对象提取器从每个获得的图像中提取至少一个。 令人讨厌的数据发生器产生出现的摄像机和运动物体出现的出现时间,并且对于多个摄像机,消失相机和移动物体消失的消失时间。 令人难以置信的数位存储了多台摄像机出现的摄像机和出现的时间以及消失的摄像机和移动物体的消失时间。 拓扑推断器使用出现的摄像机和出现的时间以及消失的摄像机和移动物体的消失时间来推测网络的拓扑。 因此,该设备使用相机精确地估计多个摄像机的网络中的多个摄像机之间的拓扑和距离,以及移动物体出现和消失的出现和消失时间。 结果,该装置准确地跟踪网络中的移动物体。