NTechLab's new Software Identifies Suspects Based on Their Emotions

By Prei Dy, | May 11, 2017

Police authorities are looking on employing emotion recognition technology to capture suspects. (YouTube)

An emotion reading technology, created by NTechLab, could soon help police authorities pre-emptively stop criminals and potential terrorists.



"The recognition gives a new level of security in the street because in a couple of seconds you can identify terrorists or criminals or killers," Alexander Kabakov, NTechLab CEO, said.




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The emotion recognition tool, which is part of the company's facial recognition software, has an accuracy rate of over 94 percent, NTechLab said. The software could reportedly monitor citizens for suspicious behaviors by tracking their identity, age, gender, and even current emotional state. This could give the software capabilities to fight crimes in real time.



Meanwhile, NTechLab refused to comment where the technology is being applied, but it could generally be installed for CCTV cameras. Kabakov also noted that privacy is not an issue for the technology, saying "If you're in a public space, you have no privacy."



He further added that with the advent of smartphones, expectation of privacy has disappeared. "We don't have privacy because phones know so much about you, including your behavior and location."



Last year, NTechLab made headlines after its facial recognition software was used to power the FindFace app to trace people on Russia's Facebook-like Vkontakte from a photo.







NTechLab also revealed it has raised $1.5 million to be used for research and development. It aims to use the funds to develop more real world and cloud applications for the facial and emotion recognition software.



Currently, the Russian firm NTechLab has more than 2,000 international clients including Australia, China, India, the UK, and US.



NTechLab, however, is not the first tech firm to create such technology. But it is won two university awards for its accurate face and emotion recognition, beating tech giants such as the likes of Google and Facebook. It also won the EmotioNet challenge of the University of Ohio.

