Zero-VIRUS* - Zero-shot Vehicle Route Understanding System for Intelligent Transportation.

CVPR Workshops(2020)

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摘要
Nowadays, understanding the traffic statistics in real city-scale camera networks takes an important place in the intelligent transportation field. Recently, vehicle route understanding brings a new challenge to the area. It aims to measure the traffic density by identifying the route of each vehicle in traffic cameras. This year, the AI City Challenge holds a competition with real-world traffic data on vehicle route understanding, which requires both efficiency and effectiveness. In this work, we propose Zero-VIRUS, a Zero-shot VehIcle Route Understanding System, which requires no annotation for vehicle tracklets and is applicable for the changeable real-world traffic scenarios. It adopts a novel 2D field modeling of pre-defined routes to estimate the proximity and completeness of each track. The proposed system has achieved third place on Dataset A in stage 1 of the competition (Track 1: Vehicle Counts by Class at Multiple Intersections) against world-wide participants on both effectiveness and efficiency, with a record of the top place on 50% of the test set.
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关键词
zero-shot vehicle route understanding system,vehicle counts,real-world traffic scenarios,vehicle tracklets,real-world traffic data,AI City Challenge,traffic cameras,traffic density,intelligent transportation field,city-scale camera networks,traffic statistics,Zero-VIRUS
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