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Alcatraz AI’s Facial Authentication Enables Frictionless Access Control

Larry Anderson
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Related Links
  • Can Microchip Implants Replace Plastic Cards In Modern Access Control?
  • Artificial Intelligence: What’s Next For AI And The Cloud In Physical Security?
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Effective access control can be achieved without the use of cards using a new generation of secure facial authentication enabled by artificial intelligence and machine learning. Alcatraz AI is introducing a system that deploys a sensing device, about the size of a badge reader, with multiple color and infrared cameras that can detect facial features and confirm an identity.

Real-time 3-D facial mapping avoids anyone using a photograph, video or mask to spoof the system and confirms there is a real person that matches the stored facial image.

System Helps In Tailgating Mitigation

Deep neural networks, powered by NVIDIA, enable the system to achieve new levels of frictionless access control, says Vince Gaydarzhiev, CEO of Alcatraz AI. Computer processing is achieved at the edge to ensure speedy and secure access control.

We saw an opportunity to create a system that solves issues of tailgating and addresses the need for security without increasing friction"“We saw an opportunity to create a system that solves issues of tailgating and addresses the need for security without increasing friction,” says Gaydarzhiev. The accuracy of the system lessens the need for security guards, he says.

The Silicon Valley startup, currently with 20 employees, was founded in early 2016 by a team from Apple, NVIDIA and Lily Robotics with a goal of targeting mid- to large-sized corporations that currently have deployed badging systems. The company has raised close to $6M from venture capital firms and individuals, and Johnson Controls/Tyco has invested in the startup.

Alcatraz AI’s sensor device, mounted near a door, confirms a user’s identity and communicates the user’s badge number to the existing access control infrastructure. “The system improves the facial profile every time, using the neural network to be even more accurate in the future,” says Gaydarzhiev. He says it is the industry’s first “instant one-factor authentication for multi-person in-the-flow sensing.”

 

In the future, the frictionless system simply recognises the user and opens the door
The system is less expensive than previous facial authentication systems and does not require users to be very close to the reader

Easy Enrollment And Deployment

Enrollment in the system is easy. Companies can deploy a separate enrollment station, or any reader can be used for enrollment. After badging in a couple of times, the face matching system “enrols” the face with the associated badge number, thus allowing the user to dispense with the badge altogether.

In the future, the frictionless system simply recognises the user and opens the door. A user company can quickly deploy the system at locations where thousands of employees have access, without requiring employees to go to HR for enrollment.

Gaydarzhiev says accuracy of the system is no less than that of iris scanning, and the accuracy is configurable for specific needs. He says the system is less expensive than previous facial authentication systems and does not require users to be very close to the reader. Facial authentication is also more flexible than iris scanning or fingerprinting.

Detecting Intent From Positioning Of Eyes

The system detects intent from the positioning of the eyes and body to avoid opening a door unintentionallyIn contrast to near field communication (NFC) or Bluetooth systems, the technology does not require a compatible smart phone or have issues of communication range. There is no need for users to stop and perform an action or gesture to signal intent. The system detects intent from the positioning of the eyes and body to avoid opening a door unintentionally, says Gaydarzhiev. 

Alcatraz AI is targeting high-tech enterprises, including healthcare, government and eventually banks. Currently they have three pilot installations among large global software companies and are undergoing trials with some government agencies. Today, they sell direct to end users, but the intent is to develop a dealer channel that will account for most of the sales.

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  • Network / IP
  • Biometrics
  • Healthcare security
  • Security installation
  • Security access systems
  • Biometric authentication
  • Facial recognition systems
  • Iris recognition systems
  • Security guards
  • Fingerprint recognition
  • Bank security
  • Door access control
  • Near Field Communication
  • IR cameras
  • Artificial intelligence (AI)

Author profile

Larry Anderson
Larry Anderson Editor, SecurityInformed.com & SourceSecurity.com

An experienced journalist and long-time presence in the US security industry, Larry is SecurityInformed.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 SecurityInformed's team of dedicated editorial and content professionals, guiding the "editorial roadmap" to ensure the site provides the most relevant content for security professionals.

People mentioned in this article

Vince Gaydarzhiev
Vince Gaydarzhiev Alcatraz AI
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New Pelco CEO Optimistic About Iconic Company’s Path Forward
New Pelco CEO Optimistic About Iconic Company’s Path Forward

Kurt Takahashi, the new CEO of Pelco, says he will provide collaborative leadership to help build the Pelco team, work together hand-in-hand with team members, remove barriers and lead the company forward. He brings industry experience and relationships to the new post that will translate into new opportunities. Takahashi joins Pelco from AMAG Technology, where he served as President for the last couple of years. Earlier, he had stints at ADT, Tyco and Quantum Secure, where he was Global Vice President of Sales and Marketing. “This was an opportunity to join a brand that has deep, rich and far-reaching history,” says Takahashi. “I couldn’t resist the opportunity to come into a company such as Pelco and be able to make a difference.” Improving the fundamentals Takahashi acknowledges that Pelco has slipped in the last 10 years from its position as a market-leading brand. To address the situation going forward, the company must “improve fundamental things,” he says. Those fundamentals include keeping the customer first, putting the right people in the right roles, and executing technical support well. Keeping the customer first, putting the right people in the right roles, and executing technical support well  “We have to provide customer service from when we receive an order, to acknowledging it, to processing it and shipping the order,” says Takahashi. “Another piece is to deliver revisions to a product in a faster time period and introduce new products to the market in a timely way. In terms of market presence, we learn that people haven’t really heard from Pelco in a while. We have to get in front of integrators and consultants more aggressively than we have in the past.”   “It’s up to us to prove that we belong and can sustain and support customers moving forward,” he adds. “We will get new opportunities, but we will need to execute them. If we do that, we will grow.” Brand optimism Takahashi sees more reasons for optimism. “In spite of the problems, we are a big company with thousands of customers, a massive footprint, 10 offices around the world and people in over 40 countries. We are a strong, known brand around the world. These are a great foundation to grow from; we just have to execute better.” These are a great foundation to grow from; we just have to execute better Pelco’s new parent company, Transcom Capital Group, was another reason Takahashi was attracted to the position. He says Transom is led by “amazing professionals” that specialize in “transformational culture and how to diffuse best practices in an organization.” At Pelco, Transom has already led surveys, workshops and focus groups throughout the organization to create a vision, mission and values covering how the company wants to present itself in the market. From those values will emanate new process and policy improvements to move the company in the right direction. New visions and missions The company’s new, collectively developed vision is “to make the world safer.” The mission is “to deliver distinctive video solutions and world-class customer experiences.” The company’s new, collectively developed vision is “to make the world safer.” The company’s culture is built on six values: innovation and excellence, customer focus, integrity, respect and recognition, collaboration, and ownership. “We believe this is what will help drive our culture moving forward, and it’s the mindset of all of us as one team with one goal that will give us something to be proud of,” says Takahashi. “As we move into the new era of Pelco, you will see excitement internally and externally,” he adds “Everybody’s really eager to see Pelco come back and be a significant player.” Three horizons to success The idea is to look inward and improve on the current, successful product lines Takahashi sees three horizons that summarize the company’s path to future success. The first horizon is to focus on the fundamentals of what the company does today. The idea is to look inward and improve on the current, successful product lines, such as the VideoXpert video system and on-board video analytics. The second horizon will be to look at ways to advance the current feature set, whether “to build, partner or buy.” Building partnerships will be part of that success, such as the partnerships they are already building with Briefcam and Anyvision. The third horizon will be to expand their innovation, based on feedback from end users, dealers and consultants. “I want to get very deeply connected with our customer base,” says Takahashi. “Are we on the right path? Should we explore other partner relationships? We need to bring those minds together to expand our vision.” The focus should be on solving three business problems – mitigating risk, ensuring compliance and saving money. Looking ahead to ISC West in the spring, Takahashi expects Pelco to emerge as a more proactive company that is eager to engage. “We have a lot of stories to communicate, and we have not been as active as we should,” he says.

Which Security Markets Are Likely To Embrace The Cloud?
Which Security Markets Are Likely To Embrace The Cloud?

Cloud applications are an everyday facet of business these days, exemplified by systems such as Office 365, Salesforce.com and Dropbox. The physical security market is also embracing the cloud after overcoming some initial concerns and thanks to improvements in cloud offerings. We asked this week’s Expert Panel Roundtable: Which security markets are likely to embrace the cloud?

Can AI Video Analytics Ever Really Be Intelligent?
Can AI Video Analytics Ever Really Be Intelligent?

Video surveillance is commonly associated with security. But in most cases, it's used to record incidents and assist in investigations after the fact rather than prevent undesirable events. Artificial intelligence–powered video analytics is a highly promising trend that fundamentally changes the way things work. Extracting manageable data from a video stream can help recognize risky situations early on, minimizing damage and, ideally, completely avoid emergencies. At the same time, AI significantly expands the areas of application of video surveillance beyond security systems. AI significantly expands the areas of application of video surveillance beyond security systems However, the hype around this new, trendy technology prevents the potential user from choosing quality solutions in a wide variety of products. This often leads to over-expectation, followed by a complete let-down. Can AI-powered video analytics really be the key to a technological breakthrough in video surveillance? We'll take a look at what the technology can do, what it can't, and where it can go from here. Technological breakthrough or just another bubble? It's often said that the video management software (VMS) market is becoming increasingly commoditized and widely available. A lot of products with similar features (or, at least, similar promises from the manufacturer) make it hard to choose. As a result, vendor names and reputations are turning into one of their primary selling points. Manufacturers have two choices available: get wrapped up in a price war and rely on cutting expenses, or offer a product that's truly innovative and revolutionary. Manufacturers have two choices available: get wrapped up in a price war, or offer a product that's truly innovative and revolutionary VMS developers who choose the second route are gravitating towards creating products that use artificial intelligence based on neural networks and deep learning. Emerging two or three years ago, the AI video analytics market is experiencing a boom in growth. This new tech wave has stirred the still, stagnant backwaters of the VMS world and gave small, ambitious developers something to be optimistic about. It seems they now have a chance to emerge as market leaders in the next few years. However, the hype around this popular trend is raising reasonable concerns among experienced security industry professionals. These concerns come from clients looking for a solution to their problems, and from suppliers building a long-term development strategy. This largely resembles another tech bubble, like the one built up around pre-AI video analytics and burst when it became clear that the sensational promises around it were pure marketing hype (and rather unscrupulously so). However, there are a lot of factors that indicate that AI-powered video surveillance systems aren't another bubble. The three factors The first — and the main one — comes from systems already in place on customers' sites. They fulfill the same promises made during the previous bubble by hotheads in a rush to teach the computer to analyze events in real time using a classical algorithmic approach. The second is the fact that this new technology has seen investment from not only software and cloud startups, but also established VMS developers. Even giants like Intel, which has presented a full line of neural network accelerator hardware and a set of software tools that streamlines working with them, specifically in the field of computer vision. This new technology has seen investment from not only software and cloud startups, but also established VMS developers The third factor lies in artificial intelligence's abilities. AI plays chess, drives cars, and works wonders in many other fields. Why shouldn't it be applied to video monitoring and analysis? What AI can do Just what can artificial intelligence do in video surveillance systems at this stage of development? It can't quite analyze a sequence of events and understand the "logic" of what's happening in the cameras' field of view. At least not yet. But it's probable that AI will learn to do this in the next few years. But neural network analytics can already detect, classify, and track objects very well, providing high accuracy even in busy scenes. Artificial intelligence can be used in the real world to: detect smoke and flames for early fire warning at open areas (forest, open warehouse, parking lot, etc.); distinguish people/vehicles from animals and other moving objects, e.g. to protect the perimeter of a nature park from poachers; distinguish a person in a helmet and protective clothing from a person without them to prevent accidents at a dangerous production facility or construction site; count objects of a specific type, e.g. cars in a parking lot, people in the sales floor, wares moving on a conveyor belt, etc. in non-security-related solutions. Those are just a few examples. After training a neural network, it can tackle other, similar tasks, too. Generally, a neural network trained in specific conditions isn't replicable. In other words, it won't work as well under different conditions. On the other hand, developers have learned how to quickly train AI for the needs of a specific project. The most important requirement is having enough video footage. Somewhat apart from that is the use of neural networks in facial and automatic number-plate recognition. This is an example of reproducible neural networks (train once, deploy everywhere), which makes them more appealing commercially. If non-reproducible neural networks have only recently become economically feasible due to the rapid evolution of specialized hardware (aforementioned Intel's product, for example), then the use of AI in facial recognition and ANPR has been well established for a long time. The use of AI in facial recognition and ANPR has been well established for a long time Another kind of AI analytics that we'll explore is behavior analytics. This function, probably more than any other, is bringing video surveillance systems closer to understanding what's happening on camera. Its potential is vast. How Behavior Analytics Works From a technical point of view, behavior analytics combines artificial intelligence with a classic algorithmic approach. A neural network trained on a multitude of scenarios can determine the position of the bodies, heads, and limbs of humans in the camera's field of view. The algorithm outputs an array of data containing descriptions of their poses. Conditions can be set for data to detect a specific pose, such as raised hands, prostrated or crouching persons. Developers can use this to quickly create new detection tools to identify potentially dangerous behavior specified by a government or business client. There's no need for additional training of the neural network. How Behavior Analytics Can Be Deployed Someone crouched down next to an ATM could be a technician, CIT guard, or burglar. Bank security should be notified in any of the cases. A person in shooter position, together with a bank employee or cashier with their hands raised could indicate a robbery. The system can be configured to automatically send alerts with a surveillance snapshot to the police so they can assess the threat and take action if needed. It's vital that the police receive the alert, even if the employee is unable to activate the alarm. In many cases, attention should be directed to a prostrate individual. This could be somebody who needs immediate help, or it could be someone sleeping in an inappropriate public place, for example, a 24/7 ATM space. Behavioral analytics can also be used to ensure workplace safety. For example, tracking whether employees are holding the handrails when using the stairs at a manufacturing facility or a construction site. What Now? Behavior analytics can be deployed wherever your clients' imagination takes them. With this feature, practically any pose that indicates potentially dangerous behavior can be detected. Timely response to an alarm helps avoid material damages or, in other situations, casualties. Practically any pose that indicates potentially dangerous behavior can be detected An area of potential development for behavior analytics is the ability to analyze a sequence of poses by the same person or a combination of poses and relative positions of several individuals. That will be the next level of evolution in AI's use in video surveillance: moving from "detecting" to "understanding" behavior in real time. In its most basic form, this type of analytics can be deployed to detect deviations from the search procedure in correctional facilities when a person being inspected must assume a pre-defined sequence of poses. A more advanced form allows it to detect any kind of abnormal behavior, such as a brawl breaking out in a public space. Ideally, behavior analytics can predict dangerous situations based on nearly imperceptible cues gleaned from collected statistics and a Big Data analysis. At the moment, this sounds like pure fantasy, but what seemed like whimsy not too long ago is now a reality with AI. It's already beaten humans in chess and the game of Go (Weiqi). Will artificial intelligence be able to outplay humans at charades one day? It's entirely possible that we'll soon see for ourselves.

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