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Video surveillance applications using multiple views of a scene

机译:使用场景的多个视图的视频监控应用

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Automatic video surveillance techniques are used to detect intruders within a scene. This task is mostly reduced to the problem of detecting moving objects evaluating image sequences of a monocular camera. An essential problem of this monocular approach is its inability to measure the 3D-size and 3D-position of objects reliably, as object size and velocity are estimated within the 2D-image plane. To include 3D-information about the scene an approach using a second camera is proposed in this paper which combines the evaluation of the measurement data of the two cameras using an efficient 3D-scene model. Here, two cameras are used with an overlapping field of view, which represents an installation often used in existing video surveillance applications. It is shown that using the combined evaluation of the two cameras, the false detection rate in the case of moving shadows, leaves, birds and insects or blindings can be further reduced compared to a pure monocular evaluation.
机译:自动视频监视技术用于检测场景中的入侵者。该任务主要减少到检测运动物体以评估单眼相机的图像序列的问题。这种单眼方法的一个基本问题是,由于无法在2D图像平面内估算对象的大小和速度,因此无法可靠地测量对象的3D大小和3D位置。为了包括有关场景的3D信息,本文提出了一种使用第二台摄像机的方法,该方法使用高效的3D场景模型结合了对两台摄像机的测量数据的评估。在这里,使用两台具有重叠视场的摄像机,这代表了现有视频监控应用中经常使用的设备。结果表明,使用两个摄像机的组合评估,与纯单眼评估相比,可以进一步减少在移动阴影,树叶,鸟类和昆虫或盲目情况下的错误检测率。

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