Artificial Intelligence, Computational Vision, and Bioinformatics at UHV

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Efficient Video Surveillance

In this project we are recruiting individuals to observe some surveillance videos and detect events in them. We are studying the performance of human operators in visual surveillance tasks.

A software tool is developed that helps detect potential events in video surveillance images. Upon the detection of potential events, the area in which the event may occur may be highlighted to direct the attention of human observers. The performance improvement achieved by employing such tools will be investigated throughout this study.

We will further investigate the limitations of human visual perception in observing simultaneous images that contain many visual stimuli. This will lead us to develop more efficient tools and techniques. These algorithms will further enhance human visual surveillance experience by addressing cognitive and visual challenges human operators face in such applications.