{"id":72067,"date":"2016-04-18T13:59:12","date_gmt":"2016-04-18T17:59:12","guid":{"rendered":"https:\/\/www.ucf.edu\/news\/?p=72067"},"modified":"2024-08-22T15:01:26","modified_gmt":"2024-08-22T19:01:26","slug":"undefined-32","status":"publish","type":"post","link":"https:\/\/www.ucf.edu\/news\/undefined-32\/","title":{"rendered":"Crime-Scene Video Analysis Goes High-Tech with $1.3 Million Grant to UCF"},"content":{"rendered":"
A $1.3 million grant from the National Institute of Justice is funding a new two-year project that may revolutionize the way police monitor and analyze crime-scene surveillance video footage with technology developed at the 海角直播.<\/p>\n
For the first time, UCF computer scientists will develop and test computer-vision technology that will automate the process of monitoring and reviewing thousands of hours of video streams fed from multiple cameras. The technology will be developed to work quickly to handle the large volume of data generated by the cameras, and will significantly reduce the burden placed on human investigators who perform the work and may produce faster leads for some criminal investigations.<\/p>\n
Computer vision is a field within computer science that uses computers to quickly recognize and analyze patterns, gestures, facial features and objects in images such as photographs and videos. Cameras are already commonplace in public areas from airports to streets and the video feeds are constant.<\/p>\n
The research team, led by Mubarak Shah, UCF Trustee Chair professor of computer science and director of the Center for Research in Computer Vision, also includes Raymond Surette, professor of criminal justice at UCF, and researchers from Columbia 海角直播.<\/p>\n
The team will develop the technology using archived and live video clips supplied by the Orlando Police Department to build algorithms so that computers will have the ability to recognize and flag out-of-the-norm actions, gestures, events and behaviors that could indicate criminal activity.<\/p>\n
For example, in video footage of the 2013 Boston Marathon bombing, the suspect was the only person in the large crowd who did not look back when an explosion ignited behind him.<\/p>\n