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Event analysis based on multiple video sensors for cooperative environment perception

机译:基于多个视频传感器的事件分析以实现协同环境感知

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Safety is considered as one of the most crucial aspects in the modern transportation domain. In this paper, we benefit from the videos captured by multiple external video sensors from infrastructure, and propose an algorithm to perceive the environment via these data from different aspects. The algorithm consists of two parts: the descriptor for representing the event and the classification method for analyzing the scenes. The covariance matrix feature descriptor is proposed to fuse the optical flow and the intensity of the image, and the nonlinear one-class SVM with a multi-kernel strategy is used to detect the unusual events in the scene. The method is applied to analyze events in the video surveillance dataset with promising results obtained.
机译:安全被认为是现代交通领域中最关键的方面之一。在本文中,我们将从基础设施的多个外部视频传感器捕获的视频中受益,并提出了一种算法,可以通过这些数据从不同方面感知环境。该算法由两部分组成:用于表示事件的描述符和用于分析场景的分类方法。提出协方差矩阵特征描述符,融合图像的光流和强度,并采用非线性多类策略的一类支持向量机检测场景中的异常事件。该方法用于分析视频监控数据集中的事件,并获得了有希望的结果。

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