Passenger Abnormal Behaviour Detection using Machine Learning Approach

In this paper we have proposed the clustering approach to classify the random walk trajectories from the synthetic bus station video. Bus station one of the most crowded locations that consist of more than thousands of passengers or travelers waiting for the buses to travel to the destination point. These crowded locations can be highly prone to accidents or terrorist activities. Work is classified into two steps i.e Firstly we find out the trajectories from the image by using the machine learning approach after that we apply the agglomerative clustering algorithm which is used to group the abnormal trajectories with the similar spatial patterns and normal trajectories with similar spatial patterns.

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Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024)