Facial recognition has seen huge breakthroughs since the U.S. National Institute of Standards and Technology (NIST) first began testing in 2010. Accuracy has seen massive gains, especially from 2013-2018.

In the 2018 test, the most accurate algorithm was 20 times more accurate than the 2013 equivalent. Essentially, 95 percent of the matches that failed in 2013 now yield correct results. Compare that to 2010-2013, when the most accurate algorithm reduced its error rate by 30 percent. This reduction in error rates since 2013 is due to wholesale replacement of the old algorithms with new ones based on deep convolutional neural networks — completely revolutionising the technology.

Optimal recognition results

SAFR says it delivers optimal recognition results with 99.86 percent accuracy in under 100 milliseconds

One entrant in the newly energised market is RealNetworks, whose SAFR for Security is an AI-based facial recognition solution for live video that integrates video management system (VMS) solutions. With 24/7 monitoring, SAFR detects and matches millions of faces accurately in real time, enabling teams to manage a watchlist across any number of video feeds.

SAFR says it delivers optimal recognition results with 99.86 percent accuracy in under 100 milliseconds, even in real-world conditions where faces are in motion, at different angles, under poor lighting, or partially obscured. SAFR builds on RealNetworks’ 23-year history in video technologies. Launched in July 2018, SAFR — secure, accurate facial recognition — is enabling new applications for security, convenience, and analytics.

Create security responses

We seek to be the world’s most trusted facial recognition platform and are delighted to partner with customers in the security industry and elsewhere to shape a more secure, convenient future worldwide,” says Dan Grimm, Vice President of Computer Vision and General Manager of SAFR at RealNetworks. “Security professionals are asked to keep us safe 24/7, monitoring a burgeoning number of cameras, and we help make them more effective.”

SAFR targets facial recognition for live video, identifying camera-unaware faces moving in real-world conditions. In the April 2019 NIST results, SAFR tested as the fastest and most compact solution among algorithms with less than 0.022 False Non-Match Rate — 62 percent faster than the average speed, according to the company. SAFR now provides capabilities such as live video overlays alerting security professionals to events in real time, automatic bookmarks with rich metadata for investigative work, and alerts that can be customised to create security responses.

SAFR says they have achieved a balance of accuracy and performance for live video
SAFR uses one-sixth the compute power of competing facial recognition solutions

Facial recognition algorithms

Five years ago, facial recognition algorithms would struggle to match forward-facing people from still images, let alone camera-unaware moving faces from live video with variations in rotation and tilt. SAFR says they have achieved a balance of accuracy and performance for live video. A contributor to this accuracy is consistency across a range of skin tones. The algorithm was trained on a highly diverse global set of over 10 million non-simulated real-world faces.

SAFR was optimised for speed and can sample a face multiple times during the same period of time as other algorithms, subsequently increasing its accuracy. SAFR achieves the performance through edge processing. Distributed architecture enables efficient bandwidth consumption, reducing the roundtrip latency of facial recognition speed to under 100 milliseconds. The savings lower total cost of ownership (TCO): SAFR uses one-sixth the compute power of competing facial recognition solutions, equating to $500,000 or so in savings on a 250-camera deployment.

Integrated experience

SAFR also uses off-the-shelf hardware and is optimised to leverage inexpensive GPUs

SAFR also uses off-the-shelf hardware and is optimised to leverage inexpensive GPUs. SAFR can be deployed on premises or in the cloud, and supports Windows, Linux, macOS, iOS, and Android. When SAFR is paired with a VMS, such as Milestone XProtect or Genetec Security Center, the integrated experience includes 24/7 monitoring to detect and match faces in real-time.

Features include live video overlays within the VMS to identify strangers, threats, concerns, unrecognised persons, VIPs, employees, or other tagged individuals in live video. Real-time alerts can be customised for when persons of interest appear on a video camera feed. Additionally, automatic bookmarks with rich metadata make for easier investigative review of security footage. Facial recognition technology is increasingly in demand to improve safety across various industry verticals.

Better customer experience

Large enterprises with high-visitor flows and heightened security — such as transportation hubs, stadiums, universities, and hospitals — need to know in real time when persons of interest or those on watchlists appear on camera. Sports stadiums could apply facial recognition to deny entry to banned patrons, locate lost children, or recognise VIPs to deliver a better customer experience.

Hospitals need access control to restricted areas and pharmaceutical storage closets

Hospitals need access control to restricted areas and pharmaceutical storage closets. Airports and transit centres value traffic flows, demographic composition, and dwell times to help improve scheduling. SAFR for Security is available worldwide, and the company partners with VMS providers such as Milestone, Genetec, Digifort, and IPConfigure by Paliton Networks. They are actively working to support additional VMS solutions and have sales teams located in major metropolitan cities around the world.

Security professionals

The job of the security professional is critical in today’s world,” says Grimm. “SAFR for Security helps mitigate the challenges of the important work security professionals do to keep us all safe.” In designing and developing SAFR, RealNetworks considered diversity and the uniqueness of each person; Grimm says their massive global training data set is a competitive advantage.

SAFR is designed with privacy in mind. All facial images and signatures are AES-256 encrypted in transit or at rest. “SAFR is powerful enterprise-grade software that is continuously improving through innovation and many years of expertise,” says Grimm.

Share with LinkedIn Share with Twitter Share with Facebook Share with Facebook
Download PDF version Download PDF version

Author profile

Larry Anderson Editor, SecurityInformed.com & SourceSecurity.com

An experienced journalist and long-time presence in the US security industry, Larry is SourceSecurity.com's eyes and ears in the fast-changing security marketplace, attending industry and corporate events, interviewing security leaders and contributing original editorial content to the site. He leads SourceSecurity.com's team of dedicated editorial and content professionals, guiding the "editorial roadmap" to ensure the site provides the most relevant content for security professionals.

In case you missed it

Panasonic AI-driven cameras empower an expanding vision of new uses
Panasonic AI-driven cameras empower an expanding vision of new uses

Imagine a world where video cameras are not just watching and reporting for security, but have an even wider positive impact on our lives. Imagine that cameras control street and building lights, as people come and go, that traffic jams are predicted and vehicles are automatically rerouted, and more tills are opened, just before a queue starts to form. Cameras with AI capabilities Cameras in stores can show us how we might look in the latest outfit as we browse. That’s the vision from Panasonic about current and future uses for their cameras that provide artificial intelligence (AI) capabilities at the edge. Panasonic feels that these types of intelligent camera applications are also the basis for automation and introduction of Industry 4.0, in which processes are automated, monitored and controlled by AI-driven systems. 4K network security cameras The company’s i-PRO AI-capable camera line can install and run up to three AI-driven video analytic applications Panasonic’s 4K network security cameras have built-in AI capabilities suitable for this next generation of intelligent applications in business and society. The company’s i-PRO AI-capable camera line can install and run up to three AI-driven video analytic applications. The AI engine is directly embedded into the camera, thus reducing costs and Panasonic’s image quality ensures the accuracy of the analytics outcome. FacePRO facial recognition technology Panasonic began advancing AI technology on the server side with FacePRO, the in-house facial recognition application, which uses AI deep learning capabilities. Moving ahead, they transitioned their knowledge of AI from the server side to the edge, introducing i-PRO security cameras with built-in AI capabilities last summer, alongside their own in-house analytics. Moreover, in line with the Panasonic approach to focus more on collaboration with specialist AI software developers, a partnership with Italian software company, A.I. Tech followed in September, with a range of intelligent applications, partially based on deep learning. Additional collaborations are already in place with more than 10 other developers, across the European Union, working on more future applications. i-PRO AI-capable security cameras Open systems are an important part of Panasonic’s current approach. The company’s i-PRO AI-capable cameras are an open platform and designed for third-party application development, therefore, applications can be built or tailored to the needs of an individual customer. Panasonic use to be a company that developed everything in-house, including all the analytics and applications. “However, now we have turned around our strategy by making our i-PRO security cameras open to integrate applications and analytics from third-party companies,” says Gerard Figols, Head of Security Solutions at Panasonic Business Europe. Flexible and adapting to specific customer needs This new approach allows the company to be more flexible and adaptable to customers’ needs. “At the same time, we can be quicker and much more tailored to the market trend,” said Gerard Figols. He adds, “For example, in the retail space, enabling retailers to enhance the customer experience, in smart cities for traffic monitoring and smart parking, and by event organisers and transport hubs to monitor and ensure safety.” Edge-based analytics offer multiple benefits over server-based systems Edge-based analytics Edge-based analytics offer multiple benefits over server-based systems. On one hand, there are monetary benefits - a cost reduction results from the decreased amount of more powerful hardware required on the server side to process the data, on top of reduction in the infrastructure costs, as not all the full video stream needs to be sent for analysis, we can work solely with the metadata. On the other hand, there are also advantages of flexibility, as well as reliability. Each camera can have its own individual analytic setup and in case of any issue on the communication or server side, the camera can keep running the analysis at the edge, thereby making sure the CCTV system is still fully operational. Most importantly, systems can keep the same high level of accuracy. Explosion of AI camera applications We can compare the explosion of AI camera applications to the way we experienced it for smartphone applications" “We can compare the explosion of AI camera applications to the way we experienced it for smartphone applications,” said Gerard Figols, adding “However, it doesn’t mean the hardware is not important anymore, as I believe it’s more important than ever. Working with poor picture quality or if the hardware is not reliable, and works 24/7, software cannot run or deliver the outcome it has been designed for.” As hardware specialists, Figols believes that Panasonic seeks to focus on what they do best - Building long-lasting, open network cameras, which are capable of capturing the highest quality images that are required for the latest AI applications, while software developers can concentrate on bringing specialist applications to the market. Same as for smartphones, AI applications will proliferate based on market demand and succeed or fail, based on the value that they deliver. Facial recognition, privacy protection and cross line technologies Panasonic has been in the forefront in developing essential AI applications for CCTV, such as facial recognition, privacy protection and cross line. However, with the market developing so rapidly and the potential applications of AI-driven camera systems being so varied and widespread, Panasonic quickly realised that the future of their network cameras was going to be in open systems, which allow specialist developers and their customers to use their sector expertise to develop their own applications for specific vertical market applications, while using i-PRO hardware. Metadata for detection and recognition Regarding privacy, consider that the use of AI in cameras is about generating metadata for the detection and recognition of patterns, rather than identifying individual identities. “However, there are legitimate privacy concerns, but I firmly believe that attitudes will change quickly when people see the incredible benefits that this technology can deliver,” said Gerard Figols, adding “I hope that we will be able to redefine our view of cameras and AI, not just as insurance, but as life advancing and enhancing.” i-PRO AI Privacy Guard One of the AI applications that Panasonic developed was i-PRO AI Privacy Guard Seeking to understand and appreciate privacy concerns, one of the AI applications that Panasonic developed was i-PRO AI Privacy Guard that generates data without capturing individual identities, following European privacy regulations that are among the strictest in the world. Gerard Fogils said, “The combination of artificial intelligence and the latest generation open camera technology will change the world’s perceptions from Big Brother to Big Benefits. New applications will emerge as the existing generation of cameras is updated to the new open and intelligent next generation devices, and the existing role of the security camera will also continue.” Future scope of AI and cameras He adds, “Not just relying on the security cameras for evidence when things have gone wrong, end users will increasingly be able to use AI and the cameras with much higher accuracy to prevent false alarms and in a proactive way to prevent incidents." Gerard Fogils concludes, “That could be monitoring and alerting when health and safety guidelines are being breached or spotting and flagging patterns of suspicious behaviour before incidents occur.”

What is the best lesson you ever learned from an end user?
What is the best lesson you ever learned from an end user?

Serving customer needs is the goal of most commerce in the physical security market. Understanding those needs requires communication and nuance, and there are sometimes surprises along the way. But in every surprising revelation – and in every customer interaction – there is opportunity to learn something valuable that can help to serve the next customer’s needs more effectively. We asked this week’s Expert Panel Roundtable: what was the best lesson you ever learned from a security end user customer?

What is the impact of remote working on security?
What is the impact of remote working on security?

During the coronavirus lockdown, employees worked from home in record numbers. But the growing trend came with a new set of security challenges. We asked this week’s Expert Panel Roundtable: What is the impact of the transition to remote working/home offices on the security market?