Most people who own a mobile phone or have an online banking account know what facial recognition technology is even if they do not use it. With the help of artificial intelligence (AI), the software identifies or confirms someone's identity by scanning heir face. Once activated, facial recognition makes user authentication easier and faster when someone logs into a site or uses their mobile device. Unfortunately, facial recognition is not foolproof. Malicious parties continue to find ways to spoof their way past interfaces that use facial recognition and hack protected sites and devices.

Paravision has released new software development kits (SDKs) to facilitate the design and deployment of embedded facial recognition systems based on its edge AI (artificial intelligence) technology. Edge AI solutions for facial recognition are already powering several devices on the market that are both ultra-low power and small form factor, as well as extremely fast and accurate. The new toolkits released by Paravision now support several facial recognition functions, including face detection, landmark detection, image quality assessment, liveness and anti-spoofing, template creation, and 1:1 or 1:N face matching. Commenting on the news, the computer vision firm said the above facial recognition functions can be integrated with backend systems in a hybrid architecture. In other words, a system built via the Edge AI SDK could potentially run face detection, quality metrics, liveness, and image cropping on the edge while enabling face matching itself in the cloud.

Are you interested in learning about Artificial Intelligence and Machine Learning? If so, this FREE webinar is for you. Dr Temitope Sam-Odusina (Computer Vision and Artificial Intelligence Engineer) and Dr Abbas Egbeyemi (Software Engineer) will give an overview of Artificial Intelligence and Machine Learning via real-life examples and applications and a live demonstration on how to develop a facial recognition application. The webinar will take place on Saturday 5th September 2020 at 6:00 PM (West Africa Time) via Zoom (Zoom link will be provided after registration) and will be hosted by Dr Adeayo Sotayo. Any programming experience will be beneficial.

If I asked you to name the objects in the picture below, you would probably come up with a list of words such as "tablecloth, basket, grass, boy, girl, man, woman, orange juice bottle, tomatoes, lettuce, disposable plates…" without thinking twice. Now, if I told you to describe the picture below, you would probably say, "It's the picture of a family picnic" again without giving it a second thought. Those are two very easy tasks that any person with below-average intelligence and above the age of six or seven could accomplish. However, in the background, a very complicated process takes place. The human vision is a very intricate piece of organic technology that involves our eyes and visual cortex, but also takes into account our mental models of objects, our abstract understanding of concepts and our personal experiences through billions and trillions of interactions we've made with the world in our lives. Digital equipment can capture images at resolutions and with detail that far surpasses the human vision system.

While facial recognition has been on mobiles for a while, some newer utilizes include in maintenance and entrance systems for offices and homes, together with retail programs. Imagine walking into a shop where a robot greets you by name, tells you your internet order is prepared, and then indicates other products you may want pickup.Facial recognition is making that possible as the technology increases traction in a variety of consumer goods, cars, and retail and resort services, along with its longstanding but contentious usage of law enforcement and safety.While facial recognition has been on smartphones for a while, some newer utilizes include in maintenance and entrance systems for offices and homes, together with retail programs. SoftBank Robotics chief strategy officer Steve Carlin, that revealed CES attendees how the business's Pepper robot could provide retail clients personalized attention, said the technology may also be utilised in resorts where an automatic system could provide a personalized experience to a normal customer."They Abe Chen of this Chinese-based automobile startup Byton stated its car, set to start later this season, would have the ability to produce helpful recommendations based on facial recognition."It Carriere said retailers could personalize advertisements on electronic signals by employing this technology -- a teenage girl may not observe exactly the identical message as an older man.Additional startups were incorporating facial recognition to house doorbells or safety systems, allowing relatives and friends to acquire entrance whilst alerting homeowners about possibly questionable men and women."That is an additional element of freedom on your smart house," explained Bill Hensley of this security company Nortek, who revealed the way its brand new Elan system could certainly assist people in and customize the home atmosphere.Chinese startup Tuya introduced its own AI movie doorbell utilizing real-time facial recognition to identify relatives, friends, couriers, land supervisors and even pets, and also to make a"whitelist" of approved individuals."You It stores information on the unit to lessen risks of information leakage.Additional CES exhibitors such as Procter & Gamble were demonstrating using facial recognition to allow clients to customize skin care remedies. Even as the applications for facial recognition increase, the technologies remains contentious, particularly about law enforcement building databases up.Some critics worry about the truth of the tech and if it means more types of surveillance and monitoring.Retailers and other companies"might already have each data point around me my face," Brenda Leong of the Future of Privacy Forum at Washington explained."So

The Facial Recognition Technology Is Known to Have Gained a Foothold in Many Industry Verticals and It Keeps on Continuously Charting New Ground. Facial Recognition has gained so much traction in an entire host of verticals and applications (according to Variant Market Research, its market is expected to be worth some $ 15.4 billion by 2024) that most anyone, regardless of the kind of business they are in, should look into whether the technology could come in handy in reaching their business objectives. In part, this is owing to the ability of the Facial Recognition technology to better equip and advance the field of expertise known as Marketing, - something universal and of the utmost importance to most industries. Moreover, Face Recognition can make a dent in precisely those areas of Marketing, in which the now rampant Digital Marketing falls short, or is, simply, irrelevant. What are those areas, how much headway has been made already and what are the potentialities one should be aware of?

If you are already using a pre-curated dataset, such as Labeled Faces in the Wild (LFW), then the hard work is done for you. You'll be able to use next week's blog post to create your facial recognition application. But for most of us, we'll instead want to recognize faces that are not part of any current dataset and recognize faces of ourselves, friends, family members, coworkers and colleagues, etc. To accomplish this, we need to gather examples of faces we want to recognize and then quantify them in some manner. This process is typically referred to as facial recognition enrollment. We call it "enrollment" because we are "enrolling" and "registering" the user as an example person in our dataset and application.