Facial recognition technology doesn’t need a formal introduction. We have come across some form of facial recognition technology by now. From the authentication access to your professional data in your office to even unlocking your smartphone, facial recognition technology has entered and has become part and parcel of our life now. The presence of this technology doesn’t just end there.
Now even the governments of many countries are officially adopting it in one form or another for various purposes. Facial recognition technology was first introduced, back in mid 6os. Woody Bledose, Helen Chan Wolf, and Charles Bission were the pioneers of this technology. It has surely evolved over the years.
Now that we have seen the impact and the importance of the facial recognition technology, let us now take a look at some of the key open source facial recognition software that have transformed the facial recognition technology beyond our wildest of imaginations.
Inspired by famous sitcom Person of Interest, OpenFace Tracker is one of the leading market tools. It can detect face from a picture and video too. It is integrated with the open source APIs like OpenCV and supports the Windows based systems.
OpenFace uses a deep learning facial recognition model. Torch computing framework is the system to run the data offline and prevents the workload of doing the training time and again. As the tool uses a real-time analysis through Google’s FaceNet, the accuracy of the tool is commendable.
The OpenEBTS is an open source project and managed by ImageWare Systems. As it is an open source, anyone is welcomed to participate in project for betterment of products. The main aim of OBI (Open Biometrics Initiative) is advancement in the products related to biometrics as it is spreading it roots towards public, private and academic sectors.
OpenEBTS can be availed on Windows 32 and 64 bits as well as Linux and Android. Some of its core features are manager to peer recognition, face grouping, peer to peer recognition, predictive analysis, facial coordinates. It is a free of cost application and provides on-site training. In case if customer requires support they can generate online ticket. For small businesses it is pinnacle tool.
iFace is considered as the leader of biometric technology. iFace is not restricted to only face recognition but it also supports finger print sensors along with time attendance system. Product is comes with a 5.7 inches 4.3 TFT touch screen and 630MHz high-speed multi bioprocessor.
In one product, customer can avail multiple features. Some of its core features are like built-in privacy protection, face grouping and peer to peer recognition. This is a web based tool as it is an Open API and you can host it on-premises. Pricing model is based upon requirements of clients. In case, you require any guidance then it will provide you on-site training. iFace team will provide you support via emails and phone. This tool is useful for small and medium businesses.
vFace is known for its toughness and build quality. Doesn’t matter how poor is environment (lightning, darkness, etc.) its high accuracy will detect your face and finger prints. vFace comes with face detection, time and attendance portal compatibility. Controls of the tools are simple to understand and it can easily integrate with your on-premises system. vFace just not depends upon retina check but it also captures size and shape of your eye, nose structure, bones and jaw features for perfect accuracy.
It comes with infra-red optical system which can detect you in any environment. 3 inches TFT screen with 9 digit user id. For different organization and project this is easy to use. vFace can provide specialized applications for banking, defense and corporate sector. Finger print sensor is enabled for computer security. Some additional features are like 200 face capacity, 10,000 card capacity, facial coordinates, diversity recognition, built-in privacy protection. It is a web-based application. You can find support on emails and phone where its pricing model is quoted.
Flandmark tool is an open source C library. For static images facial detection, this tool is considered to be one of the best.
Some of its core features are predictive analysis and facial coordinates. This tool is supported by both Windows and Linux. You can find help guide for training but they also provide on-site training. Support is available via online ticket and email. If you are a start-up then this tool will help you in lots of ways but most importantly it’s completely free.
Face++ is providing three kind of facial detection security i.e face detection, face comparing and face searching. Face detection we’ve already covered, so let’s try to understand other features. Suppose there are two similar looking employees in your organization, Face++ will provide you with great accuracy to detect both the face. Response time of this tool is in milliseconds as it searches through its archive repository and provide you access.
With many other features let’s discuss some of its core feature. Face++ provides you with pre sales support and tech support. On-site training with API documents and blogs for your easy understanding. Pricing model is on the requirements of clients.
OpenBR stands for open source biometric recognition. It works in 4 parts detection, normalization, representation, extraction and by combing all above aspects it provide matching. While detection it focus on eyes, face structure, keypoints and landmark. During normalization it focus on color conversion, enhancement wherever it requires, filtering and registration. For representation it focus on local binary patterns, keypoints descriptors, orientation histogram, wavelets. During extraction it covers face clustering, normalization, subspace learning, and vector quantization which helps in generating features.
Let’s discuss some of its core features. It support Windows, Mac, Linux. Available with peer to peer recognition, face grouping, predictive analytics, manager-to-peer recognition. Free of cost and provides help guide and on-site training. Customers can get support via email and it is applicable for small scale businesses as well as freelancers.
DeepFace is an emerging organization in field of facial recognition. DeepFace mostly focuses on face detection, face attributes analysis, emotion analysis and facial expression. This tools can detect the human face from images and show its results in high-precision face bounding boxes. For face attributes it cover age, gender, head pose, eye status, skin colour etc. This is a highly accurate, efficient and reliable tool.
Some of its core features include age detection, built in privacy protection and performance management. It supports Windows, Mac and another variant is web based. For deployment, it is cloud hosted. For customer support it provide, live chat, phone call during business hours. But most importantly it is suitable for small, medium and large businesses.
As a human, we do facial recognition every day, probably for us it is not a hard task at all because it almost a daily routine habit for us but for a computer system it is a complex job. So step by step we will try to understand the algorithm of facial recognition in simple language.
First: It requires photo or video in which you appeared. It won’t be a concern if it’s you only who’s there in the picture or if it’s a group photo along with your friends. With facial recognition tool, your image will cropped upto your face only. This is just like when you are clicking profile image.
Second: In this step, facial recognition tool takes the measurements of your face which includes both eyes, size of chin, forehead, nose and it can also recognize your facial landmarks. Algorithm of tool can also analyse features of cheek bones and jaw. Facial landmark could be any lines, scar, mole etc. on your face. Some best tools in business can define 68 landmarks.
Third: Your facial signature is combined with mathematical formula, deep learning concepts and Convolutional Neural Networks for accurate results. A recognition test runs in the database of familiar faces which could be in a police or military database or any other source.
Convolutional Neural Network emerges as far better than the traditional algorithm of facial recognition.
Facial recognition and face detection are two different streams but from last two decades both are at their peak. Just not for law enforcement or secret services but also for the corporate. Above mentioned open source tools for facial recognition which definitely can add security and reliability to your business.