AI, cloud and facial recognition

3 trends in video content analytics for 2019

Editor, IFSEC Global

Author Bio ▼

Adam Bannister was Editor of IFSEC Global from 2014 through to November 2019. Adam is also a former Managing Editor at Dynamis Online Media Group.
January 2, 2019

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The 2022 State of Physical Access Control Report

Video analytics software is a well-established feature of modern video surveillance systems.

The days of relying exclusively on the round-the-clock vigilance of security guards have long since passed.

In one remarkable case study a murder investigation was solved in minutes using video analytics.

Nevertheless, we’re still arguably in the foothills of what these systems could achieve in terms of exploiting the unfathomable volume of video data captured daily by millions of security cameras around the world.

The technology shaping the next leap forward – and accelerating the pace of change – is one that will drive dramatic change in all areas of society: AI.

Alternately known as deep learning or machine learning (though these three terms don’t all mean precisely the same thing), AI has been deployed in physical security technologies for a few years already.

But it remains a young technology and the CEO of a pioneer in this field believes AI will effect considerable change in the industry in 2019.

“AI is making it possible for businesses and law enforcement to make proactive, data-driven decisions to increase operational efficiencies.” Trevor Matz, CEO, BriefCam

With 2019 now underway Trevor Matz, CEO of BriefCam, offers three predictions for what trends we can expect to see in video surveillance and video content analytics this year, with AI, along with facial recognition and the cloud, to the fore.

Video content analytics is moving beyond old-fashioned detective work, according to Matz, also president of Canon-owned BriefCam.

 “Video content analytics software that incorporates artificial intelligence (AI) and deep learning technology is now valuable for much more than after-the-fact investigations,” he argues. “Because of the incredibly fast speed and intelligent capabilities, many are finding new ways to use it.”

He cites the following examples of how AI-driven video content analytics software will be applied:

  • Retail businesses leveraging it for proactive, strategic planning to enhance the shopping experience, yielding higher sales and greater customer loyalty
  • Healthcare organisations addressing operational challenges like finding unauthorised people in restricted facility areas
  • Transportation hubs improving passenger flow and municipalities proactively keeping city streets safer

Matz continues: “AI is making it possible for businesses and law enforcement to make proactive, data-driven decisions to increase operational efficiencies, as well as giving them the ability to recognise and prevent potential issues before they arise.”

Despite misgivings among civil liberties groups (which can be assuaged by the industry), facial recognition will continue to be adopted in greater numbers, by a wider range of applications, in 2019.

“Facial recognition is big development that is here to stay,” he says. “Made possible by deep learning and AI technology, facial recognition can log you into your smartphone and identify your friends in your social media photos.

“And as we think of video content analysis, facial recognition is playing an increasingly significant role. In 2019 we’ll see more law enforcement organisations using video analytics with facial recognition to solve incidents much faster and retailers immediately identify shoplifters.

“As it proliferates throughout our world, and the technology becomes more readily available, we expect significant adoption in 2019.”

Finally, Matz, who has been at the helm of BriefCam since July 2017, believes edge processing and cloud computing will drive acceleration in adoption of advanced video content analytics.

“As video continues to gain popularity, the need to conserve bandwidth is driving a surge in cloud migration and edge computing,” he explains. “This opens up the possibility for advanced video content analytics that process data collected from cameras and devices.

“In 2019, we anticipate a continued migration to cloud computing and edge processing and as a result, we’ll see AI-backed video content analytics become much more widely adopted in many industries such as transportation, higher education, healthcare, retail and more.”

BriefCam is a developer of ‘video synopsis’ and deep learning solutions for rapid video review and search, smart alerting and quantitative video insights. Transforming raw video into actionable intelligence the US-based company creates solutions for law enforcement and large enterprises that not only enhance safety and security but also identify operational efficiencies.

Sergeant Johnmichael O’Hare of the Hartford Police Department is one impressed customer. “Using BriefCam has been a game changer for our city,” he has said. “Just last week, BriefCam helped us catch a suspected child predator by enabling us to review two hours of surveillance videos in 13 seconds.”

The importance of deep learning to the future of video analytics was also a central theme of a talk delivered at IFSEC 2018.

Briefcam is showcasing its and deep learning ‘video synopsis’ solutions at the 2019 edition of IFSEC International, which is Europe’s largest annual trade show for the physical security industry.

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