A motion-based image processing system for detecting potentially dangerous situations in underground railway stations |
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| Institution: | 1. Digital Imaging Research Centre, Faculty of Computing, Information Systems and Mathematics, Kingston University, Penrhyn Road, Kingston upon Thames, Surrey KT1 2EE, United Kingdom;2. Ipsotek Ltd., P.O. Box 54055, London SW19 4WE, United Kingdom;3. Centre for Transport Studies, University College London, Gower St, London WC1E 6BT, United Kingdom;1. Urban Institute, 2100 M St. NW, Washington, DC, 20037, United States;2. Ned Levine & Associates, United States;3. New York University, United States;1. SpaceTimeWorks, San Diego, CA, USA;2. Medical Center, University of Nebraska, Omaha, NE, USA;3. Department of Mathematics, Xavier University, Cincinnati, OH, USA;4. Earth and Life Institute, Environmental Sciences. Université catholique de Louvain, Louvain-la-Neuve, Belgium;5. Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan;1. Department of Biomedicine, University of Aarhus, Aarhus, Denmark;2. The Water and Salt Research Center, University of Aarhus, Aarhus, Denmark;3. Institute of Clinical Medicine, University of Aarhus, Aarhus, Denmark;4. Research Unit for Molecular Medicine, Aarhus University Hospital, Skejby, Denmark;5. Department of Biochemistry and Cell Biology, School of Medicine, Kyungpook National University, Daegu, Korea;6. Department of Pharmacology, University of Copenhagen, Copenhagen, Denmark;1. School of Computer Science and Technology, Harbin Institute of Technology, China;2. Microsoft Research, Beijing, China |
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| Abstract: | The timely detection of potentially dangerous situations involving passengers in public transport sites is vital to improve the safety and confidence of the travelling public. Conventional CCTV systems are monitored manually so that a single observer is typically responsible for dealing with tens or hundreds of cameras at a time. Thus, important events might be missed or detected too late for effective action. This paper gives an overview of motion-based methods used in a system developed as part of a EU-funded research project, to detect three important situations of interest to public transport operators. The style has been kept intentionally general so as to provide a good broad understanding of the transport needs being addressed. Emphasis is given to the performance of these methods as assessed with a large set of video recordings supplied by metropolitan railway networks in London, Paris and Milan. |
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