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- W2551937385 abstract "In recent years, with the latest technological advancements, off-the-shelf cameras became vastly available, producing a huge amount of content that can be used in various application areas. Among them, visual surveillance receives a great deal of interest nowadays. Until recently, video surveillance was mainly a concern only for military or large-scale companies. However, increasing crime rate, especially in metropolitan cities, necessitates taking better precautions in security-sensitive areas, like country borders, airports or government offices, schools and colleges. Human face and human behavioural pattern play an important role in person identification. Visual information is a key source for such identifications. The proposed system aims to identify abnormal head motions, thereby prohibiting copying. It will also identify a student moving out of his place or swapping his position with another student or looking into another student's computer . We aim to develop a system that will identify the students who indulge in malpractices/suspicious activities during the course of an online examination. The system automatically detects suspicious activities and alerts administration." @default.
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- W2551937385 date "2013-01-01" @default.
- W2551937385 modified "2023-09-23" @default.
- W2551937385 title "Automated Video Surveillance to Detect Suspicious Human Activity" @default.
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