Top 19 Facial Recognition Technologies

Facial Recognition Technologies

In recent years, biometric tools like facial recognition technologies have witnessed some groundbreaking innovations. From unlocking your mobile phone to automatically tagging photographs to diagnosing patients with genetic conditions, the possibilities are now endless.

The research firm Markets and Market expects the global facial recognition market to be worth $8.5 billion by 2025. However, the success of all these face recognition tools depends largely on adequate training data. In this scenario, the more extensive and more inclusive the data is, the better.

But before we get ahead of ourselves, let’s first define it.

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What Is Facial Recognition Technology?

At its most basic, face detection tools match faces in photographs and video stills to existing identities saved in a database. This technology essentially detects or finds a face in an image, maps it for analysis, and recognizes or confirms an individual’s identity. An excellent example of this in action is photo tagging (which most of us have encountered).

As facial features are far more complex than other biometric technologies like fingerprints and iris scanners, face detection tools require highly sophisticated artificial intelligence (AI) algorithms.

You can also use these smart algorithms with complex AI-powered analytics tools to do more with them. For example, Google’s Derm Assist can identify skin conditions by leveraging AI and machine learning (ML).

Tip:

Data for training your facial recognition technology such as photos and videos can be obtained quickly and individually from clickworker.

More about Image Datasets More about Video Data Sets

So, what are the best face recognition models available today? Let’s take a closer look.

1. Amazon Rekognition

Amazon Rekognition is a leading name in the face recognition software game. Rekognition can be used to engage in facial analysis, face search for verification, and to identify people and objects by labeling them.

This facial recognition tool can recognize as many as 100 people in a single image. One of the reasons for this is the fact that it can perform face matches against databases with millions of faces.

As the company already has massive datasets at its disposal, AI and ML algorithms are able to learn and then accurately identify them. Users can also extend their recognition capabilities through custom labeling.

Amazon Rekognition: Pricing depends on usage, and a free tier is available.

2. DeepFace

Facebook announced its DeepFace program way back in 2014. This face detection tool can determine if faces in two photographs are the same with a 97.35% rate of accuracy. This turned out better than the tools used by the FBI that had an accuracy rate of 85%.

While there isn’t a commercial rollout of this facial identification software, a framework exists on GitHub with the same name. This library also supports more accurate technologies like Google’s FaceNet.

While you can leverage its robust REST API, it only supports verification methods. This means that you can’t put together your own face collection and expect it to pick your face out of it. However, it could prove to be a lot of fun if you’re a Python developer.

DeepFace pricing: free and open source.

3. Face++

China’s Megvii Technology’s Face++ facial recognition platform can not only recognize faces but also provide what they call a “Beauty Score.” However, the company hasn’t revealed how it all works. Other services include age estimation, emotion recognition, gender recognition, and landmark detection.

Companies can add Face++ to their technology stack, but it’s important to note that it cost twice more than other leading services. But the good news is that it supports the widest variety of software development kits (SDKs), including:

  • C++
  • Java
  • Javascript
  • iOS
  • Matlab
  • PHP
  • Python
  • Ruby

Face++ pricing: Starts at USD 100 per day, and a free version is available.

4. Microsoft Azure Cognitive Services Face API

Microsoft’s Face API is one of the allows businesses to embed facial recognition into their apps. This approach makes it one of the best face recognition models as it helps companies provide seamless access and secured user experiences without reinventing the wheel or breaking the bank.

What’s great about this face detection tool is its ability to perceive facial features and attributes like beards, facemasks, and glasses. Microsoft Azure’s Face API SDK supports Go, Java, Node.js, .NET, and Python.

For additional features like age estimation, emotion recognition, and more, Microsoft offers both a self-hosted version and a software-as-a-service option.

Microsoft Face API pricing: depends on usage, and a free plan with 30,000 free requests per month is available.

5. Kairos

Kairos developed this AI-powered facial recognition tool to enable safe and enhanced customer experiences. The company provides both web services and an SDK that businesses can integrate into their own solutions.

What’s different about Kairos is the fact it can also track important demographic data. As a result, it has been quite popular among industries like automotive, banking, capital management, healthcare, and market research.

Kairos is best for enterprises looking to optimize the facial recognition features of their mobile applications. This is because you’ll need significant expertise to get the most out of this smart solution.

Kairos pricing: Plans start at $19 per month for students, and a free 14-day trial is available.

6. SenseTime

SenseTime is another powerful face detection software developed in China. Besides face recognition, SenseTime also provides body analyzing technology. It can use 14 body feature points and recognize different body parts, and it can also do it while someone is moving.

The liveness detection feature in SenseTime helps improve user verification protocols. Whenever companies use it, they have a better chance of preventing spoofing attacks.

This AI-powered tool is also better suited for companies that have more video-based facial recognition needs.

SenseTime pricing: available upon request.

7. Trueface.ai

Trueface.ai offers face detection in three different modes like container, plug-and-play, and SDK. Beyond identifying faces, Trueface.ai can also detect weapons, perform live verifications and space analytics.

As such, this tool is popular in education, fintech, hospitality, retail, and security, where safety and security are paramount. You can also use this tool for temperature detection, which can be vital during times like the recent COIVD-19 pandemic.

Trueface.ai provides robust solutions for different government agencies around the world. While this face identification software required a lot of coding expertise in the beginning, the latest plug-and-play option makes it accessible to everyone.

Trueface.ai pricing: Available upon request.

8. Oz Liveness

Oz Liveness is an innovative facial recognition and authentication technology that private companies and government agencies use worldwide to prevent identity theft and fraud. It protects against deepfakes and spoofs.

Oz Liveness uses sophisticated algorithms to detect many forms of biometric spoofing. These include 3D and 2D faces, photos, and videos displayed on iPads or laptops.

This technology was approved to meet the needs of the market’s most demanding customers, making it one of the best face recognition models out there. It ensures that the organization can quickly identify whether an individual is legitimate or not. It also reduces compliance risks and fraud.

Oz Liveness pricing: available upon request.

9. Cognitec

Cognitec‘s live video scan feature lets your system detect faces within live video streams. It then numbers each face detected and records the associated demographic information. This particular solution also has a large enterprise edition designed for big businesses.

There is also an ID biometrics verification solution for businesses and government agencies. Cognitec use case examples include physical security, law enforcement, and identity management.

Algorithmic optimization has resulted in superior independence of facial features such as pose, mimicry, age variation, hairstyle, glasses, or temporary lighting change.

Cognitec pricing: available upon request.

10. Sensory

The combination of face biometric authentication and voice recognition creates a highly secure and hassle-free user experience. Sensory’s speaker verification, face recognition, and biometric fusion algorithms leverage Sensory’s deep strengths in ML, computer vision, and speech processing.

This combination of face and voice recognition helps fortify security protocols while remaining quick, convenient, and highly user-friendly. Sensory also ensures the highest verification rates per user and is more convenient than other methods. This is because some biometric solutions sometimes accept false positives, known as “spoofing.”

Sensory’s innovative approach uses passive liveness, active liveness, or both to leverage a deep learning model that almost eliminates fraudsters using 3D masks and photos.

Sensory pricing: available upon request.

11. Paravision

Paravision is an intelligent video surveillance system that helps you identify people and objects in real-time. It provides a range of services, including face detection, face tracking, object detection, and person identification.

Paravision’s core technology is based on deep learning algorithms that allow it to perform these tasks effectively. It also offers a number of additional services like face clustering, face matching, spoof detection, phenotype analysis, and age estimation.

These capabilities make it perfect for applications like access control, biometric authentication, and border security.

Paravision pricing: available upon request.

12. Blippar

Of all the applications on this list, Blippar is a little bit different. It’s more than facial recognition software. Founded in 2011, Blippar is an augmented reality application that allows people to see digital designs superimposed onto physical items around them.

With the help of a smartphone camera, Blippar scans the environment and displays relevant information on top of what the user sees. For example, if someone were to take a picture of a book lying on a table, Blippar would recognize the title and author of the book and display additional information about it.

Blippar pricing: free.

13. Luxand

Luxand is an innovative software development firm that provides a wide range of facial recognition products. While these tools can help companies automate tasks, they’re best suited for programmers building applications for AI systems. These include Java, .NET, and C++ developers looking for ways to detect faces and recognize them.

Other industries that may benefit from Luxand’s technology include those involved in banking, biometrics, and the entertainment industry. These sectors can utilize Luxand’s technology to streamline processes involving face recognition.

Luxand pricing: available upon request.

14. Clarifai

Clarifai is a that specializes in ML-powered facial recognition. Their goal is to make computers smarter through data analysis and automation. They aim to improve people’s safety and reduce business risks by using facial recognition technology.

Clarifai’s technology can automatically recognize faces and align them with landmarks from any angle. Banks, governments, and retailers widely use their software to prevent theft and robbery.

Clarifai pricing: starts at $30 per month, and a free community version is also available.

15. iProov

Cybersecurity firm iProv offers biometrics-based authentication to its online users. With high security, privacy, usability, and reliability, it’s widely used in various sectors, including public and government institutions, financial services, digital identities, and travel providers, among others, which makes iProv one of the best face recognition models available at the moment.

iProov’s Face Verifier is an innovative remote face recognition application that allows organizations to verify a customer’s face against an enrolled biometric template. With this, iProov simplifies the process of verifying users through facial scans, eliminating the hassle associated with passwords and one-time passcodes. iProov can also be used for primary, multi-factor, or step-up authentication purposes.

iProov pricing: available upon request.

16. TrueKey

Developed by Mcafee security, Truekey utilizes biometric technology, using facial recognition software or fingerprint scanning to protect and manage passwords. It encrypts data with the AES-256 encryption method and multi-factor authentication to protect data against third-party intervention.

As TrueKey leverages the AES-128 encryption method, only the user can decrypt and access their own information with their chosen factors. As such, it’s the most robust encrypted data storage system available in the marketplace. TrueKey also auto-saves and enters passwords for the users once they have been identified through multi-factor authentication.

TrueKey pricing: available upon request.

17. Sky Biometry

Sky Biometry is an AI-based API and facial recognition service provider that helps businesses automate human identification processes. They offer enterprise-grade facial recognition, attribute determination, and facial detection solutions.

Sky Biometry can identify gender and age based on facial features. It can also determine facial expressions and detect objects on the user’s face. The Sky Biometric service is ideal for companies with their own developers who only require the Sky FRS API to integrate into their applications. The tool offers different subscription options and a demo version that gives users an overview of the software’s capabilities.

Sky Biometry pricing: starts at €50 per month, and a free option is available.

18. Digipass

Developed by OneSpan, Digipass is an identity verification system with a two-step verification process that utilizes biometric data, including face scans and fingerprints, to verify device users’ identities.

These features allow the user to scan a QR code from the website they intend to use. A face scan through the device’s camera follows. The scan gets compared with the stored biometrics template using ML algorithms within the application.

Digipass for Apps is an optional add-on for Android, IOS, Windows, and Linux. You can integrate it into any app to strengthen digital security. Digital Passwords are one of the most effective first-line defenses against hacking attempts and have a proven track record of stopping them.

Digipass pricing: available upon request.

19. FaceFirst

FaceFirst is a leading biometrics company providing solutions to help businesses protect themselves against fraud, theft, and violence. Their facial recognition technology allows companies to prevent identity theft and reduce shoplifting. It also provides an easy-to-use app that scans faces quickly and verifies customer identities and ages.

As a face-matching technology with a high degree of precision, FaceFirst enjoys patronage among businesses such as casinos, airport terminals, and sports arenas. These types of organizations require the software to reduce the rate of denied access to business premises.

FaceFirst pricing: available upon request.

There are more facial recognition technologies available in the marketplace. As the industry evolves, you can bet that there will be an explosion of similar tools. However, to engage in accurate face detection, you must train AI and ML algorithms using large datasets representing different races, genders, age groups, emotions, and more.

Ethical Considerations and Debates

The rapid advancement and widespread adoption of facial recognition technology has sparked intense ethical debates and public concerns. Key issues include:

Privacy and Surveillance

Critics argue that facial recognition enables unprecedented levels of surveillance and tracking, potentially infringing on personal privacy and freedom of movement. There are concerns about how biometric data is collected, stored, and potentially shared without consent.

Bias and Discrimination

Studies have shown that many facial recognition algorithms exhibit racial and gender biases, with higher error rates for women and people of color. This raises serious concerns about fairness and potential discrimination when the technology is used for law enforcement or access to services.

Consent and Transparency

Questions remain about whether individuals can meaningfully consent to having their biometric data captured and analyzed, especially in public spaces. There are also calls for greater transparency around how facial recognition systems work and are deployed.

Potential for Misuse

While facial recognition has legitimate uses, there are fears it could be misused for oppressive surveillance, tracking of marginalized groups, or exploitation of personal data by bad actors if proper safeguards aren’t in place.

Proponents argue that facial recognition, when implemented responsibly, can enhance security, streamline processes, and even save lives. However, many experts and advocacy groups call for stronger regulation and ethical guidelines to address these concerns as the technology continues to evolve.

Technical Achievements and Benchmarks

Facial recognition technology has made significant strides in recent years:

Accuracy Rates

Top-performing algorithms now achieve over 99.9% accuracy on standard benchmarks like the NIST Face Recognition Vendor Test (FRVT). Error rates have decreased dramatically, especially for 1:1 verification tasks.

Speed and Scale

Modern systems can process millions of faces per second, enabling real-time identification in large crowds or against massive databases. Cloud-based solutions allow for rapid scaling.

Low-Light and Partial Face Recognition

Advanced algorithms can now identify individuals in poor lighting conditions or with only partial facial features visible, expanding potential use cases.

Liveness Detection

To combat spoofing, many systems now incorporate sophisticated liveness detection to differentiate between real faces and photos or masks.

Edge Computing

On-device processing allows for facial recognition without transmitting sensitive data, addressing some privacy concerns.

While impressive, it’s important to note that performance can vary significantly in real-world conditions compared to controlled tests. Ongoing research aims to further improve accuracy, reduce biases, and enhance privacy protections.

Facial recognition is part of a broader ecosystem of biometric identification methods:

Iris Recognition

Analyzing the unique patterns in a person’s iris can provide even higher accuracy than facial recognition for some applications, though it typically requires more controlled conditions.

Fingerprint Scanning

A well-established biometric, fingerprint recognition remains widely used for its reliability and relative ease of implementation.

Voice Recognition

Identifying individuals by their unique vocal characteristics offers a non-visual alternative, useful for phone-based authentication or voice-controlled systems.

Gait Analysis

Emerging technology can identify people by their walking pattern, potentially useful for long-range identification.

Multimodal Biometrics

Many advanced systems now combine multiple biometric factors (e.g., face + voice) for enhanced security and accuracy. This approach can help mitigate some of the weaknesses of individual methods.

While each technology has its strengths, facial recognition remains prominent due to its balance of accuracy, convenience, and non-intrusiveness for many applications. However, the integration of multiple biometric modalities is likely to become increasingly common as systems evolve.

FAQs on Facial Recognition Technologies

How is facial recognition technology used?

Facial recognition technology is used in a variety of ways, including security and surveillance, access control, marketing, and social media. The most common facial recognition technology uses biometrics, which measures and analyzes human physical and behavioral characteristics.

What are some common technologies in facial recognition?

There are many different technologies that can be used for facial recognition, but some of the most common include 2D matching, 3D mapping, thermal imaging, and retinal scanning.

What are common challenges for facial recognition technologies?

There are a number of common challenges that can impact its accuracy. These include poor lighting, obscured faces, changes in facial expression, and facial hair as well as those with low contrast features. Additionally, facial recognition can be fooled by things like glasses, hats, and scarves.

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Andrew Zola