Passenger Abnormal Behaviour Detection using Machine Learning Approach

• Autorzy: Dabral Sonal , Agarwal Amit , Kumar Sachin , Gautam Bhaskar

Identyfikatory

DOI

10.15439/2017R113

• Konferencja: The Second International Conference on Research in Intelligent and Computing in Engineering
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

path detection; anomaly detection; trajectories; clustering

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2017
• Tom: Vol. 10
• Strony: 21--25
• Opis fizyczny: Bibliogr. 25 poz., fot., rys., tab., wykr.

Twórcy

autor

Dabral Sonal

• Computer Science & Engineering Department, Dehradun, Graphic Era University

autor

Agarwal Amit

• Computer Science & Engineering Department, Indian Institute of Technology Roorkee

autor

Kumar Sachin

• Centre for Transportation Systems, Indian Institute of Technology Roorkee

autor

Gautam Bhaskar

• 4Computer Science & Engineering Department, National Institute of Technology Karnatak

Bibliografia

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