Beyond the shadow of a doubt, facial recognition technology has completely transformed the world we live in. Growing security concerns due to threats of terrorism and contact tracing to stop the spread of COVID-19 has not just boosted the adoption rate of the technology. But it has turned facial recognition into a multi-million-dollar industry. According to the statistics published by HNS the market is forecasted to reach a staggering figure of $12.67 Billion by the end of 2028.
From medical to smart security apps, facial recognition technology is helping in building a secure and healthier future. Before we dig deeper into the top face recognition apps, being used by industries and individuals globally. Let’s take a look at various scenarios in which these apps might prove to be handy.
6 Common Uses of Facial Recognition Apps
The global facial recognition market is forecasted to grow by a CAGR of 15.4% by 2028, due to rapid adoption by industries like retail, security and banking. Here’s a look at some common uses of these apps.
Unlock Mobile Devices
Most technological companies make use of facial management systems for their gadgets so that the owner of those gadgets enables them as added protection.
This highly versatile software plays a crucial role in helping the police track and identifies criminals by making use of their images and matching them to a live feed.
Find a Missing Person
The face match of people notifies the police and helps in recovering missing people.
Validation of Identity at ATMs
Facial recognition apps can verify the individuals who are trying to make transactions through ATMs, ensuring an ultimate level of security.
Social Media Identification
Social media platforms make use of this highly-effective technology to identify people in photos so that it becomes easy for them to decide whether they want to be tagged in that photo or not.
If you want to know more about how face recognition apps work, here’s a video from Interesting Engineering showcasing how face recognition apps work, and their uses within different domains.
Top Face Recognition Apps for iOS and Android in 2023
It is one of the popular applications when it comes to face recognition applications specifically in law enforcement and the military. It matches photographs of the entire personnel against their databases. This application is primarily used for finding out the identity of individuals which can further help the enforcement officers enhance the security of the community while ensuring that they cannot get engaged in any faux arrests. Facefirst has helped some of the top retailer’s in U.S.A to reduce shoplifting by more than 34%, while the percentage of in-store violence has declined by 90%. Watch this Video from Facefirst to see how the app has helped in boasting up retail security.
It’s a face recognition application as well as an augmented reality system that can use extensive databases for identifying objects like plants, food, animals, and more. The mobile application development company has designed it in a way that recognizes people in a more personalized manner. Blippar is highly dependent on its own database rather than an external database. It is categorized into an object and face-matching application. rather than an external database. It is categorized into an object and face-matching application. Daily Mail called it “Shazam of Faces”, due to its high level of accuracy and ability to identify identical.
It’s a revolutionary healthcare application that makes use of facial recognition software for helping doctors in clinics and hospitals so that patients can be diagnosed with various genetic disorders and bioinformatics. The proprietary algorithm used by this application compares the faces of several patients that are entirely based on their morphology patterns to diagnose their genetic condition or illness.
It is an online banking mobile application that most people have to deal with and that’s what you call identity theft and ways of protecting your customers. In order to counter this major problem, most banks all over the world make use of this facial recognition application for verifying the identity of prospective clients and using online banking for all purposes. It’s a simple-to-use application where clients take pictures of their phone by using the mobile device and then the system performs an identification check by matching the faces with the images that are stored in the database the bank for enabling access to the mobile application of a chosen bank. The app currently boasts more than 300 Million user’s, and have an astounding retention rate of more than 90%. Here is a video showcasing the features that makes the app standout from the rest.
Logme Facial Recognition
It is a search engine application that is most commonly used for facial recognition. It makes use of similarities and distances for identifying the faces in a photo. In order to use Logme, you just have to upload a picture on the application that further extracts information about the faces by comparing them to other photos users have uploaded on this flexible application. You can then browse and scroll through the various faces that are available on the application. It’s a matching system that cannot be found in free-of-cost facial recognition software.
IObit AppLock is an Android face recognition application that gives potential users the ability to lock and unlock applications either via facial recognition or voice recognition software for free of cost. As a private tool, this application can help you hide personal information, data, financial details, and healthcare details so that anyone else using your phone cannot have access to confidential information. You can easily unlock those applications by either using voice verification or face verification. It ensures that your applications can only be opened on your end.
It is one of the widely known facial recognition applications with a diversified set of uses. A wide range of APIs makes the entire process exceedingly easier. If you are a social person and keep on forgetting the names of people then you can use Luxand for saving faces in the memory of the application. Also, add names just in case you want to remember someone’s name. Alongside, the FaceSDK is used by luxand making it a commendable surveillance and biometric application Its ability to recognize faces and predict gender/age makes it a comprehensive facial recognition system.
This is why some of the biggest organizations use Luxand for safety and security purposes. Even if you are looking for something entertaining, you can use this application to play around with features like hair color, facial hair, piercings, and other associated AR-related features. Its multiple face detection APIs are inclusive of facial recognition API, Face enhancement API, Avatar API, Face aging API, and Zombie API.
Conclusion – The Best Facial Recognition Application?
Based on your choice and use Luxand is counted among one of the best facial recognition applications. However, in terms of effectiveness Facefirst and Face2gene are the second most effective applications. Identify your business requirements and download the aforementioned applications to benefit yourself with one of the best technologies out there.
How can I improve the accuracy of facial recognition applications?
By focusing on the ears and facial marks of someone you can improve the accuracy by up to 6 percent. This is an exceedingly significant increase because even professional face identification systems can get it wrong when it comes to comparing photos or unfamiliar faces.
What are the main types of facial recognition?
The major facial recognition methods are 1) Feature analysis ( inclusive of neural networks and eigenfaces) and 2) Automatic processing of facial features.
What is the process of automatic face recognition?
Face recognition is most commonly described as a process that involves four steps including face detection, face alignment, feature extraction, and face recognition.
Facial recognition is counted in what type of surveillance?
It’s a high technology that matches the captured images with other facial images. For example, the ones that are already available in databases and watchlists.