Minh Tuan Doan

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Pedestrians movements have a major impact on the dynamics of cities and provide valuable guidance to city planners. In this paper we model the normal behaviours of pedestrian flows and detect anomalous events from pedestrian counting data of the City of Melbourne. Since the data spans an extended period, and pedestrian activities can change intermittently(More)
In this paper we model the normal behaviour of pedestrians over the central business district of the City of Melbourne over a long period, and then use this model to detect the anomalous distributions. We develop an approach based on frequent itemset mining as the underlying technique and construct a model in terms of correlations of pedestrian(More)
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