|In 2014, there were an estimated 245 million video surveillance cameras installed globally (HIS Markit). Real-time visual data have many applications. As researchers gain the ability to collect large amounts of visual data about the world, the true potential of data-driven research is recognized. Despite the large amount of publicly available real-time data, there are challenges that inhibit the true potential of analyzing real-time data from these cameras including identifying the cameras either statically or dynamically and identifying camera metadata once identification of individual cameras occurs.
Researchers at Purdue University have developed a method for identifying cameras on the internet; particularly, identifying public and closed circuit television cameras and the metadata associated with each in a static or dynamic manner. Examples of uses include monitoring traffic flow, viewing wildlife, detecting intruders or anomalies, and monitoring weather conditions and emergencies.
-Allows access to existing network of cameras
-Machine learning algorithm development
Jul 30, 2019
Jan 26, 2021
Mar 23, 2017
Jul 30, 2019
Purdue Office of Technology Commercialization
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