A Maltese student has successfully carried out a study on surveillance systems mostly focusing on detection and tracking of objects by identifying the different types of methods and algorithms used for extraction and analysis.

Stephanie Kristina Scicluna was awarded a Masters of Science in Telecommunications (Network pathway) from Queen Mary, University of London, for her work.

Her research investigated the use of features like estimation of motion to measure specific aspects of abnormality detection, in order to determine the similarities and differences between frames during normal events as well as when abnormalities are detected.

Her dissertation, titled ‘Abnormality detection in road scenes’investigates how optical flow can be implemented and used to measure specific aspects of abnormality on road scenes.

This project is important in the field of video surveillance in today’s technological scenario due to the increased demand of traffic security analysis. Examples of abnormalities analysed include abnormal overtaking of cars and cars driving or turning in the wrong direction among others.

Ms Scicluna was sponsored by the Strategic Educational Pathways Scholarship (STEPS), which is partly financed by the EU – European Social Fund (ESF) under Operational Programme II – Cohesion Policy 2007-2013, ‘Empowering people for more jobs and a better quality of life’.#

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