Computer vision is a field of AI that is expanding rapidly in today’s world. It needs the use of several different algorithms that are computationally intensive to train computers.
This helps the systems in interpreting and understanding the visual world. Face detection is a computer vision problem where images are converted into an array of pixels and the trained model is used to check if the image contains a face.
It is only due to recent advancements that real-time face recognition systems have become possible. There are several custom software development companies California that use this feature.
A Glance At Face Recognition Software
Facial Recognition software is used to accurately identify the faces of animals or humans via analysis of images and videos. The software creates an outline around the face first which is called the bounding box. Then, the location of the major face elements like eyes, nose, and mouth are detected.
This has wide-ranging applications from mobile app filters to identity verification. It is very common to find web applications that use this. For instance, you can consider web development companies in San Francisco.
You can very often see them being used in sectors such as media, hospitality, retail, and so on. For instance, if a person’s face is being checked against a record of facial images, the software will return a high similarity score if the faces match.
The error rate during recognition is defined using the false match rate (FMR) An FMR of .001 implies one wrong identification for every hundred images.
This makes facial recognition very popular throughout the world. Choosing facial recognition software is quite difficult as there are a plethora of options that have been launched in recent years. In addition to that, how you wish to integrate the feature in your project totally depends on you.
There are a number of factors such as what your end-application is, the development timeline available, and if there exist any special needs.
For example, a popular benchmark known as Labeled Faces in the Wild (LFW) is used for face verification. But keep in mind that the data used for this is not enough to include all possible groups of people.
This article discusses some of the best options available for you out there in the market in both free and paid categories. These options have high accuracy and there are several other measures too that make them suitable for commercial purposes.
Developed by Facebook, DeepFace is a free, open-source facial recognition framework that uses a very large dataset of faces to train the modes so that the face representation generalizes well to any other available dataset.
This ensures that it has very high accuracy and provides results in real-time. After every face detection, attribute analysis, and face processing is done.
This means that users have to simply upload an image. It will perform analysis based on characteristics such as the position of the head, eye-opening or closing, age, gender, and more. A database is thus created based on different faces. You can search the database through an image or name. This makes it easy to just integrate the feature as a web development company.
InsightFace is an open-source software library for both 2D and 3D face detection and recognition. The toolbox is mainly based on MXNet. It has support for Python. During Covid19, the developers experimented with the Retina FaceAntiCov module.
This module was developed in order to be able to identify face boxes when people have their masks on their faces. It is still being used by custom software development companies in California.
It uses the latest methods for face detection and hence, it is highly accurate. Unlike heat map-based approaches, the software gives lightweight facial landmark models with fast coordinate regression.
The learning curve is a bit high although. So, if you are a beginner, it will take you some time to get the hang of it. If you want an API for your software development, use InsightFace-REST.
FaceNet is a free, open-source face recognition software by Google. It has great documentation and there are pre-trained models available for anyone getting started.
It basically uses high-quality features from faces which are called face embeddings (low dimensional representations). Using these as datasets, you can easily train the system.
You will find it in use in older systems. Although it is still used since the accuracy is pretty good compared to numerous models, there are no latest updates. Also, there is no API available.
CompreFace is a Docker-based face detection and recognition open-source project. It can be used as a standalone server or deployed in the cloud. The setup as well as the commands to get started are pretty simple. Even a beginner can get started with it easily.
It uses deep neural networks and offers a REST API to train algorithms. There is a UI panel for better management too. Supported picture formats include JPEG, PNG, JPG, ICO, BMP, GIF, and many more.
You can control who can access your collection of images, thereby providing an additional layer of security. Whether you are discussing web development companies in Atlanta or anywhere else, this is a consideration that definitely draws more companies.
OpenFaceTracker is an open-source ( lGPLv3 license ) face detection software that allows users to detect one or more faces present in a video or picture. After the images are fetched and faces are detected in real-time, processing can be done to identify them through a database.
If you are a custom software development in NYC or even any other city, you might also want to store the data and it provides this option. Before installing this software, you need to install OpenCV3.2 and QT4. It can work on a Windows-based operating system.
OpenBR is a free (Apache 2.0 license) and popular software for face recognition, detection, as well as landmarks. Landmarking is the process of localization of different characteristic points on the detected face.
Off-the-shelf algorithms can even provide a precise estimate for age and gender simply based on the provided face. It uses the 4SF2 algorithm for accurate detection. It supports both open and closed source development.
The framework can be used for investigating new modalities as well as improving existing algorithms. Other purposes include interfacing with commercial systems, measuring recognition performance, and deploying automated biometric systems.
There is a C++-based API available that can be used for development. It can work on various operating systems and is compatible with even Raspian based systems.
Face++ uses the latest algorithms to compare faces for checking if they match with each other. It is also used to check if the face being searched is present in the already existing database. You can save the face if you want to use it in the future.
There are both APIs and SDKs available for this. The benefits are that it is highly accurate due to the anti-spoofing technique and quick as well. You can try advanced effects such as face stickers and 3D animations. Besides, you can run it for any number of faces that you want. There is a free trial available for new users before they get the license.
Kairos provides both SaaS and self-hosted (on-premises) versions for face detection and recognition. Multi-face detection ensures accurate detection of crowds, audiences, and groups as well. It also offers additional options such as landmarking, age estimation, gender recognition, among others.
The provider uses facial recognition privacy regulations to ensure safety and security. It comes with a free trial for 14 days but after that, you have to pay for both monthly subscriptions. If you exceed your limit requests, you are required to pay more money.
Clarifai is a custom facial recognition software that returns whether the image has a face based on probability. This means that if the probability is high, it is most definitely a face.
Based on the coordinate locations of facial endpoints, the faces will be enclosed in a bounding box. It can be accessed through API or SDK. It is used in several web development companies in San Francisco and many other places.
You can use it for security camera footage, photo filter apps, dating apps, digital photography, and much more. There are other solutions for images, videos, and text recognition by Clarifai apart from the face recognition model. The basic option provides numerous features but if you wish to explore it further, you will have to pay for it.
10. Deep Vision AI
Deep Vision AI allows users to detect and recognize faces in their chosen images and videos. It is quite easy to accurately find target subjects through facial matches. You can also gather demographic information based on age and gender estimation via detected faces. The software ensures higher data privacy levels and can also be used in limited connectivity environments.
Let us say that you are a custom software development companies NYC, then you need to define your requirements in advance to buy the correct plan. Prices depend on the number of features you want to use as well as the volume of data that needs to be processed. You can easily integrate it with your company’s infrastructure. Deployment options through API include cloud, local servers (on-premise), and at the edge.
FaceX offers both software as a service (SaaS) and self-hosted models to its users for face detection and recognition. Even though everything is handled by the provider in SaaS, you still need a stable Internet connection.
This is necessary if you have to send large images to a server somewhere on the Internet. In case you choose the self-hosted version, docker images are available for Enterprise customers.
Suppose you are a web development company in Chicago using a Linux Ubuntu Operating system, then these images are compatible with the system.
You can easily integrate the technology with your mobile and web applications. The face tracking feature allows users to monitor and track face movements after detection.
You can also use services such as ID and spoof detection, age estimation, gender recognition, landmark detection, and so on. The service is paid with monthly subscriptions offering a few hundred requests per day.
Amazon Rekognition is face detection and recognition software. You just have to upload images for recognition and everything else gets automatically handled.
Just like a lot of other options discussed before, this piece of software also provides additional services such as emotion recognition, landmark detection, age estimation, and gender recognition. In line with the requirements of web development companies in Atlanta and other places, you can also detect any inappropriate content.
But besides these, you can easily analyze images from cameras installed at a large scale in factories and other places. The purpose is to automatically detect if people are wearing Personal Protective Equipment (PPE) such as face covers (face masks) and whether it properly covers the nose or any other corresponding body part in other cases.
SDKs are available in Java, .Net, and Python programming languages. It offers a free trial plan for 1 year. After that, the pricing depends on the number of recognitions to be done per month.
Few Final Words:
The face recognition industry will only continue to grow in 2021, despite concerns of some people around its potential misuse. Face recognition algorithms today are far more accurate when compared to the ones developed only a few years ago.
As the demand for face recognition software is increasing these days, more and more software are becoming accessible. With so much market growth, even paid options for face recognition software are bound to become less expensive in the future.