Instant Traveling Companion Discovery Based on Traffic-Monitoring Streaming Data

Abstract

Traveling companions are object groups that move together in a period of time. To quickly identify traveling companions from a special kind of streaming traffic data, called Automatic Number Plate Recognition (ANPR) data, this paper proposes a framework and several algorithms to discover companion vehicles. Compared to related approaches, our main contribution is that the framework can instantly detect suspicious companion vehicles with their probabilities when they pass through monitoring cameras. Our framework can be used in many time-sensitive scenarios like taking surveillance on the suspect trackers for specific vehicles. Experiments show that our approach can process streaming ANPR data directly and discover the companion vehicles in nearly real time.