SenseFace - Face Recognition Surveillance Platform in Artificial Intelligence Platform

SenseFace, a face identification software developed by SenseTime, helps police officers track and locate missing elderly persons within hours of family members reporting the situation to the bureau. SenseTime tremendously aids the bureau in reducing working time and efficiently resolving difficulties. SenseTime Group Ltd (SenseTime) is a technology business that employs deep learning technology to recognize human faces, process images, recognize objects, recognize mobile vehicles, recognize human bodies, and recognize language and characters. Intelligent video analytics, identity verification, and mobile internet solutions are among the services provided by the organization. Hong Kong and China are the locations of the company's operations.

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Features

SenseFace is used by various police forces for security. To catch criminals, SenseFace systems analyse video footage. Its technology can sense the driver's actions and detect if they are falling asleep behind the wheel or not looking at the road for a dangerous period of time, in addition to offering an extra layer of protection for ride-hailing app drivers and passengers.

Face identification systems from SenseFace can read even low-quality, complicated photos and surveillance footage of big crowds in milliseconds. They can decode face profiles, partially covered and blurred photos, moving facial expressions, and facial images recorded in different situations.

SenseFace technologies are used by a huge number of police departments to examine tapes and apprehend offenders. The device also tracks the movements of drivers to see if they are falling asleep or preoccupied behind the wheel. It also has the ability to track license plates and can notify authorities if an accident is detected.

Face recognition can be performed on over 1,000 real-time safety inspection video streams with SenseFace.

It uses a database of millions of face capture photos to track down and retrieve targets. It's adaptable when it comes to tasking for different times, locations, and goals. GPU clusters are deployed in a distributed manner.