Video Surveillance Camera to Identify Criminals in Crowds Through Algorithm
The technology was developed at Russia’s Tomsk Polytechnic University in the Department of Computer Engineering.
Developer Ilya Kalinovskii
Video surveillance technology continues to get smarter.
An algorithm for surveillance cameras can automatically detect faces in a crowd has been developed by Tomsk Polytechnic University in Russia. The algorithm is said to process high resolution videos in real time and evaluate the number of people, their gender and even their approximate age.
According to the university’s press release, the algorithm uses 4K video and allows for working with video 10 times faster than existing analogs.
“This original method can work with a stream video in ultra-high resolution 4K Ultra HD format with acceptable quality and is much faster than existing analogues in the world,” said professor Vladimir Spitsyn of the Department of Computer Engineering. “This will allow automatic monitoring of the environment and quickly identifying emergency situations without operator attention and will provide highly detailed videos.”
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“In order to detect a person on his face image in the crowd, like on stadium or in subway, it is required to work with an image in scene with very high detail. 4K resolution is suitable for this purpose,” said Ilya Kalinovskii, the developer and a PhD student in the Department of Computer Engineering. “Because of the large amounts of data it is difficult even to store these videos not only to process them, not to mention intellectual analysis.”
Kalinovskii now has to develop a video surveillance camera for 4K video stream in real time. The device will automatically detect faces and transmit only significant fragments of the scene, the press release says.
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