What is facial recognition?
Facial recognition is a way of identifying or confirming the identity of an individual using an image of their face. Facial recognition systems can be used to identify people in real time, or used to identify people in photos or videos.
What are the benefits of facial recognition technology?
Some benefits of face recognition systems are as follows:
Efficient security
Facial recognition is a quick and efficient verification system. It can be faster and more convenient compared to other biometric technologies like fingerprints or retina scans. There are also fewer touchpoints in facial recognition compared to entering passwords or PINs. It supports multifactor authentication for additional security verification.
Improved accuracy
Facial recognition can be a more accurate way to identify individuals than simply using a mobile number, email address, mailing address, or IP address. For example, most exchange services, from stocks to cryptos, now rely on facial recognition to protect customers and their assets.
Easier integration
Face recognition technology is compatible and integrates easily with most security software. For example, smartphones with front-facing cameras have built-in support for facial recognition algorithms or software code.
What are the use cases of facial recognition systems?
The following are some practical applications of a face recognition system:
Fraud detection
Companies use facial recognition to uniquely identify users creating a new account on an online platform. After this is done, facial recognition can be used to verify the identity of the actual person using the account in case of risky or suspicious account activity.
Cybersecurity
Companies use facial recognition technology instead of, or in addition to, passwords to strengthen cybersecurity measures.. Face recognition software is also a convenient and accurate security tool for unlocking smartphones and other personal devices.
Airport and border control
Many airports use biometric data as passports, allowing travelers to skip long lines and walk through an automated terminal to reach their gate faster. Face recognition technology in the form of e-passports reduces wait times and can improve security.
Banking
Individuals authenticate transactions by simply looking at their phone or computer instead of using one-time passwords or two-step verification. Facial recognition can be safer as there are no passwords for hackers to compromise. Similarly, some ATM cash withdrawals and checkout registers can use facial recognition for approving payments.
Healthcare
Facial recognition can be used to control access to patient records. It can streamline the patient registration process in a healthcare facility.
Is facial recognition accurate?
Facial recognition is highly accurate in ideal conditions. There is a higher success rate in controlled settings but generally a lower performance rate in the real world. It is difficult to accurately predict the success rate of this technology, as no single measure provides a complete picture.
For instance, facial verification algorithms matching people to clear reference images, such as a driver's license or a mugshot, achieve high accuracy scores. Factors that help improve accuracy include:
• Consistent positioning and lighting
• Clear and unobstructed facial images
• Controlled colors and background
• Camera quality and image resolution
Another factor that impacts error rates is aging. Over time, changes in the face make it difficult to match photos taken years earlier.
What is a confidence score in facial recognition?
Confidence scores, also known as similarity scores, provide feedback about how similar two images are to each other. A higher confidence score indicates a higher likelihood that two images include the same person.
How can AWS help with facial recognition?
You can use Amazon Rekognition to automate image and video analysis with machine learning. Amazon Rekognition offers pretrained and customizable computer vision capabilities to extract information and insights from your images and videos. For example, you can use Amazon Rekognition to perform the following tasks:
• Detect inappropriate or unwanted content
• Analyze and detect faces in millions of photos and videos within minutes
• Add facial comparison and analysis in your user onboarding and authentication workflows to remotely verify the identity of opted-in users for whom you have identifying information
• Determine the similarity of a face against another picture or from your private image repository
Amazon Rekognition is not independently capable of identifying or verifying the identity of individuals in images or videos.
Get started with facial recognition on AWS by creating a free account today.