Using Calibrated Camera for Euclidean Path Modeling

In this paper, we address the issue of Euclidean path modeling in a single camera for activity monitoring in a multi-camera video surveillance system. The paper proposes to use calibrated cameras to detect unusual object behavior. During the unsupervised training phase, after metric rectifying the input trajectories, the input sequences are registered to the satellite imagery and prototype path models are constructed. During the testing phase, using our simple yet efficient similarity measures, we seek a relation between the input trajectories derived from a sequence and the prototype path models. Real-world pedestrian sequences are used to demonstrate the practicality of the proposed method.