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Posts Tagged ‘facial recognition’

Sensory Demos Awesome AI Mashup at Finovate!

September 28, 2017

Finovate is one of those shows where you get up on stage and give a short intro and live demo. They are selective in who they allow to present and many applicants are rejected. Sensory demonstrated some really cutting-, perhaps bleeding-, edge stuff by combining animated talking avatars, with text-to-speech, lip movement synchronization, natural language speech recognition and face and voice biometrics. I don’t know of any company ever combining so many AI technologies into a single product or demo!

Speech recognition has a long history of failing on stage, and one of the ways Sensory has always differentiated itself, is that our demos always work! And all our AI technologies worked here too! Even with bright backlighting, our TrulySecure face recognition was so fast and accurate some missed it. With the microphones and echo’s in the large room, our TrulyNatural speech recognition was perfect! That said, we did have a user-error… before Jeff and I got on stage he put his demo phone in DND mode, which cut our audio output – but quickly recovered from that mishap.

Apple erred on facial recognition

September 15, 2017

On the same day that Apple rolled out the iPhone X on the coolest stage of the coolest corporate campus in the world, Sensory gave a demo of an interactive talking and listening avatar that uses a biometric ID to know who’s talking to it. In Trump metrics, the event I attended had a few more attendees than Apple.

Interestingly, Sensory’s face ID worked flawlessly, and Apple’s failed. Sensory used a traditional camera using convolutional neural networks with deep learning anti-spoofing models. Apple used a 3D camera.

There are many theories about what happened with FaceID at Apple. Let’s discuss what failure even means and the effects of 2D versus 3D cameras. There are basically three classes of failure: accuracy, spoofability, and user experience. It’s important to understand the differences between them.

False biometrics
Accuracy of biometrics is usually measured in equal error rates or false accepts (FA) and false rejects (FR). This is where Apple says it went from 1 in 50,000 with fingerprint recognition to 1 in 1,000,000 with FaceID. Those are FA rates, and they move inversely with FR – Apple doesn’t mention FR.

It’s easy to reach one in a million or one in a billion FAs by making it FR all of the time. For example, a rock will never respond to the wrong person… it also won’t respond to the right person! This is where Apple failed. They might have had amazing false accepts rates, but they hit two false rejects on stage!

I believe that there is too much emphasis placed on FA. The presumption is random users trying to break in, and 1 in 50,000 seems fine. The break-in issue typically relates to spoofability, which needs to be thought of in a different way – it’s not a random face, it’s a fake face of you.

Every biometric that gets introduces gets spoofed. Gummy bears, cameras, glue, and tape were all used to spoof fingerprints. Photos, masks, and videos have been used to spoof faces.

To prevent this, Sensory built anti-spoof models that weaken the probability of spoofing. 3D cameras also make it easier to reduce spoofs, and Apple moved in the right direction here. But the real solution is to layer biometrics, using additional layers when more security is needed.

Apple misfires on UX?
Finally, there’s an inverse relationship between user experience and security. Amazingly, this is where Apple got it wrong.Think about why people don’t like fingerprint sensors. It’s not because too many strangers get in; it’s because we have to do unnatural motions, multiple times, and often get rejected when our hands are wet, greasy, or dirty.

Apple set the FA so high on FaceID that it hurt the consumer experience by rejecting too much, which is what we saw on stage. But there’s more to it in the tradeoffs.

The easiest way to prevent spoofing is to get the user to do unnatural things, live and randomly. Blinking was a less intrusive version that Google and others have tried, but a photo with the eyes cut out could spoof it.

Having people turn their face, widen their nostrils, or look in varying directions might help prevent spoofing, but also hurt the user experience. The trick is to get more intrusive only when the security needs demand it. Training the device is also part if the user experience.

Guest Blog – Rise of the Machines (Learning)

November 12, 2015

A really smart guy told me years ago that neural networks would prove to be the second best solution to many problems.  While he was right about lots of stuff, he missed that one!  Out of favor for years, neural networks have enjoyed a resurgence fueled by advances in deep machine learning techniques and the processing power to implement them.  Neural networks are now seen to be the leading solution to a host of challenges around mimicking how the brain recognizes patterns.

Google’s Monday announcement that it was releasing its TensorFlow machine learning system on an open-source basis underscores the significance of these advances, and further validates Sensory’s 22 year commitment to machine learning and neural networks.  TensorFlow is intended to be used broadly by researchers and students “wherever researchers are trying to make sense of very complex data — everything from protein folding to crunching astronomy data”.  The initial release of TensorFlow will be a version that runs on a single machine, and it will be put into effect for many computers in the months ahead, Google said.

Microsoft also had cloud-based machine learning news on Monday, announcing an upgrade to Project Oxford’s facial recognition API launched in May specifically for the Movember Foundation’s no-shave November fundraising effort: a facial hair recognition API that can recognize moustache and beard growth and assign it a rating (as well as adding a moustache “sticker” to the faces of facial hair posers).

Project Oxford’s cloud-based services are based on the same technology used in Microsoft’s Cortana personal assistant and the Skype Translator service, and also offer emotion recognition, spell check, video processing for facial and movement detection, speaker recognition and custom speech recognition services.

While Google and Microsoft have announced some impressive machine-learning capabilities in the cloud, Sensory uniquely combines voice and face for authentication and improved intent interpretation on device, complementing what the big boys are doing.

From small footprint neural networks for noise robust voice triggers and phrase-spotted commands, to large vocabulary recognition leveraging a unique neural network with deep learning that achieves acoustic models an order of magnitude smaller than the present state-of-the-art, to convolutional neural networks deployed in the biometric fusion of face and voice modalities for authentication, all on device and not requiring any cloud component, Sensory continues to be the leader in utilizing state-of-the-art machine learning technology for embedded solutions.

Not bad company to keep!

Bernard Brafman
Vice President of Business Development

Sensory’s CEO, Todd Mozer, interviewed on FutureTalk

October 1, 2015

Todd Mozer’s interview with Martin Wasserman on FutureTalk

TrulySecure From Sensory Becomes First Face and Voice Biometrics Technology to be FIDO UAF Certified

August 20, 2015

Santa Clara, Calif., – August 20, 2015 – TrulySecure Multimodal Biometric Authentication from Sensory, Inc. Has Been Fully Tested and Certified for Compliance with the FIDO Universal Authentication Framework Specifications V1.0

Sensory Inc., a Silicon Valley based company focused on improving the user experience and security of consumer electronics through state-of-the-art embedded voice and vision technologies, today announced that its TrulySecure™ is the first multimodal face and voice biometric authentication software to be FIDO Certified™. The FIDO (Fast Identification Online) Alliance tested TrulySecure for compliance with the FIDO UAF (Universal Authentication Framework) 1.0 specifications, which determines that implementations of the FIDO specification are uniform across products and that those products are interoperable with other products and services that support the FIDO 1.0 specifications.

“We recognize Sensory for building TrulySecure to be fully compliant with the FIDO Universal Authentication Framework specifications and are excited to add their innovative multimodal biometric authentication solution to the FIDO Alliance’s prestigious roster of FIDO UAF Certified authenticators,” said Brett McDowell, FIDO Alliance executive director. “As more enterprises, application developers and mobile device makers shift away from password authentication, solutions like Sensory’s TrulySecure multimodal biometric authentication software will continue to prove valuable as an essential, secure means of authenticating users and keeping their data safeguarded.”

Working with the FIDO Alliance to certify compliance with FIDO standards and interoperability of TrulySecure demonstrates Sensory’s commitment to advancing the current state of user authentication, by ensuring that the industry’s most secure multimodal face and voice authentication software can be easily integrated within authentication solutions from FIDO Certified™ providers. Sensory joined the FIDO Alliance in early 2015 to work alongside other companies eager to create more secure user authentication protocols. Sensory has been a strong supporter of the FIDO Alliance since its inception and has worked with companies like Nok Nok Labs to ensure the biometric authenticator portion of their authentication solution, powered by TrulySecure from Sensory, was fully compliant with FIDO UAF 1.0 specs.

“Sensory’s TrulySecure is a great example of what can be delivered with multimodal biometrics and we are happy to support the solution within our own FIDO Certified S3 Authentication Suite,” said Ramesh Kesanupalli, founder of Nok Nok Labs and FIDO visionary. “Enterprises are looking for turnkey user solutions that offer a mix of authentication methods. Working with Sensory allows Nok Nok Labs to provide its customers with a greater variety of solutions that offer superior security compared to vulnerable passwords.”

TrulySecure leverages Sensory’s deep strengths in speech processing, computer vision, and machine learning. The combination of face recognition and speaker verification to authenticate a specific individual allows users to rest assured that their device is secure, without the hassle of fumbling around with a fingerprint reader or entering a password or PIN every time they want to access it or authenticate to sites and services. Consistent with FIDO standards, TrulySecure is an on-device biometric not requiring a cloud connection. Embedded authentication is a preferred approach for consumers and businesses that don’t want their biometric information stored outside of their personal devices. Embedded biometric solutions are also preferred for their higher security and reliability compared to cloud based systems, which have proven to be vulnerable to hackers and break-ins, and undependable in low-signal/no Internet environments. In addition to the security and dependability benefits of being embedded, TrulySecure further safeguards devices and data by requiring two forms of biometrics, making it at least twice as secure as even the best fingerprint readers found on mobile devices.

The advantages of TrulySecure when compared to other biometric authentication methods include:

  • Simple touch-free authentication – users do not need to tap a screen or swipe a finger, just look at the screen and say the passphrase
  • Its fast! – embedded within software or on device, TrulyHandsfree does not require an Internet or cloud connection to work and responds instantly
  • Robust to environmental changes – works in real-world situations, including low light or high noise environments
  • Nearly impenetrable by imposters – unlike fingerprint readers, which are vulnerable to spoofing, TrulySecure features anti-spoofing techniques to eliminate the chances of an intruder getting access
  • No additional hardware costs – TrulySecure only requires a device have a microphone and a camera; nearly all smartphones, tablets and PCs already feature these components
  • No hardware to wear out – biometric sensors, such as fingerprint readers, wear out with use; since TrulyHandsfree does not rely on special sensors, there is no risk of authentication hardware failure

“We at Sensory are huge supporters of the work the FIDO Alliance has done to create an exciting consortium focused on streamlining user transactions with on-device biometrics,” said Todd Mozer, chairman and CEO of Sensory, Inc. “Promoting biometrics for more than two decades, we are pleased that our TrulySecure technology has become the first multimodal face and vision biometrics technology to be awarded the status of FIDO Certified. By working with companies across the entire authentication ecosystem to certify the interoperability of their FIDO Certified technologies with TrulySecure, we have made it even easier for companies to integrate the industry’s easiest to use and most secure biometric authentication technology within their products.”

For more information about this announcement, Sensory or its technologies, please contact sales@sensory.com; Press inquiries: press@sensory.com

# # #

About The FIDO Alliance
The FIDO (Fast IDentity Online) Alliance, was formed in July 2012 to address the lack of interoperability among strong authentication technologies, and remedy the problems users face with creating and remembering multiple usernames and passwords. The FIDO Alliance is changing the nature of authentication with standards for simpler, stronger authentication that define an open, scalable, interoperable set of mechanisms that reduce reliance on passwords. FIDO authentication is stronger, private, and easier to use when authenticating to online services with FIDO Certified™ products and services.

About Nok Nok Labs
Nok Nok Labs provides organizations with the ability to bring strong, FIDO-based authentication infrastructure to their mobile and web applications. The Nok Nok Labs S3 Authentication Suite enables organizations to accelerate revenues, reduce fraud, and strengthen security. Nok Nok Labs is a founding member of the FIDO Alliance with customers and partners that include NTT DoCoMo, PayPal, Alipay, Samsung and Lenovo. For more information, visit www.noknok.com.

Interesting Announcements from Alibaba, Google and Microsoft

March 23, 2015

This month had three very different announcements about face recognition from Alibaba, Google, and Microsoft. Nice to see that Sensory is in good company!!!

Alibaba’s CEO Jack Ma discussed and demoed the possibility of using face verification for the very popular Alipay.

A couple interesting things about this announcement…First, I have to say, with a name like Alibaba, I am a little let down that they’re not using “Open Sesame” as a voice password to go with or instead of the face authentication… All joking aside, I do think relying on facial recognition as the sole means of user authentication is risky, and think they would be better served using a solution that integrates both face and voice recognition (something like our own TrulySecure), to ensure the utmost security of their customers’ linked bank accounts.

Face is considered one of the more “convenient” methods of biometrics because you just hold your phone out and it works! Well, at least it should… A couple of things I noticed in the Alibaba announcement: Look at the picture…Jack Ma is using both hands to carefully center his photo, and looking at the image of the phone screen tells us why. He needs to get his face very carefully centered on this outline to make it work. Why? Well, it’s a technique used to improve accuracy, but this improved accuracy, trades off the key advantage of face recognition, convenience, to make the solution more robust. Also the article notes that it’s a cloud based solution. To me cloud based means slower, dependent on a connection, and putting personal privacy more at risk.  At Sensory, we believe in keeping data secure, especially when it comes to something like mobile payments, which is why we design our technologies to be “embedded” on the device – meaning no biometric data has to be sent to the cloud, and our solutions don’t require an internet connection to function. Additionally, with TrulySecure, we combine face and voice recognition, making authentication quick and simple, not to mention more secure, and less spoofable than face-only solutions. By utilizing a multi-biometric authentication solution like TrulySecure,  the biometric is far less environmentally sensitive and even more convenient!

Mobile pay solutions are on the rise and as more hit the market differentiators like authentication approach, solution accuracy, convenience and most of all data security will continue to be looked at more closely. We believe that the embedded multi-biometric approach to user authentication is best for mobile pay solutions.

Also, Google announced that its deep learning FaceNet is nearly 100% accurate.

Everybody (even Sensory) is using deep learning neural net techniques for things like face and speech recognition. Google’s announcement seems to have almost no bearing on their Android based face authentication, which came in the middle of the pack of the five different face authentication systems we recently tested. So, why does Google announce this? Two reasons: – 1) Reaction to Baidu’s recent announcement that their deep learning speech recognition is the best in the world: 2) To counter Facebook’s announcement last year that their DeepFace is the best face recognition in world. My take – it’s really hard to tell whose solution is best on these kind of things, and the numbers and percentages can be deceiving. However, Google is clearly doing research experiments on high-accuracy face matching and NOT real world implementation, and Facebook is using face recognition in a real world setting to tag photos of you. Real-world facial recognition is WAY harder to perfect, so my praise goes out to Facebook for their skill in tagging everyone’s picture to reveal to our friends and family things might not have otherwise seen us doing!

Lastly, Microsoft’s announced Windows Hello.

This is an approach to getting into your Windows device with a biometric (face, iris, or fingerprint). Microsoft has done a very nice job with this. They joined the FIDO alliance and are using an on-device biometric. This approach is what made sense to us at Sensory, because you can’t just hack into it remotely, you must have the device AND the biometric! They also addressed privacy by storing a representation of the biometric. I think their approach of using a 3D IR camera for Face ID is a good approach for the future. This extra definition and data should yield much better accuracy than what is possible with today’s standard 2D cameras and should HELP with convenience because it could be better at angles can work in the dark. Microsoft claims 1 in 100,000 false accepts (letting the wrong person in). I always think it’s silly when companies make false accept claims without stating the false reject numbers (when the right person doesn’t get in). There’s always a tradeoff. For example I could say my coffee mug uses a biometric authenticator to let the right user telepathically levitate it and it has less than a 1 in a billion false accepts (it happens to also have a 100% false reject  since even the right biometric can’t telepathically levitate it!). Nevertheless, with a 3D camera I think Microsoft’s face authentication can be more accurate than Sensory’s 2D face authentication. BUT, its unlikely that the face recognition on its own will ever be more accurate than our TrulySecure, which still offers a lower False Accept rate than Microsoft – and less than 10% False Reject rate to boot!

Nevertheless, I like the announcement of 3D cameras for face recognition and am excited to see how their system performs.