Abstract

Crowd detection using street cameras has attracted a lot of research in recent years. In this paper, we propose a simple, fast, and effective method using YOLOv3 model for crowd detection. Using image frames extracted from surveillance video, pedestrian objects are detected, counted and a warning signal is sent out when a crowd occurs. The obtained results on test data extracted from 2 data sets STCrowd, SmartCity, and our self-collected dataset confirm the feasibility of the proposed method.

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