How the Automation Process Works
A face recognition system is an application capable of performing two major tasks – identifying a person based on key parameters and verifying their identity and authorization using a database. This technology weaves artificial intelligence and machine learning together to create a sophisticated solution.
Face recognition systems vary in terms of their functionality and unique features, but generally the process of automating your system with face recognition software requires the same basic steps.
First, you place a camera in position and start streaming video. If possible, use a motion-activated camera. This will prevent constant video streaming from overloading the face recognition server. The camera should be placed in such a way that the lens gets enough light and the user looks at the camera. If getting a complete look at the user’s face is not possible, the camera should have as clear a resolution as possible.
Next, you need to split the video into frames or individual images. Ideally, you’d improve photo quality before sending the images to the face recognition service, which you can easily do by adjusting the settings on your camera. To ensure accuracy, compare the results the server provides from different frames of the same person – if a face recognition result is different for the same face, there is likely an error or the face is unknown. Then you’ll know that you need to adjust your camera or other settings.
What Tools Can You Use?
There’re a lot of tools on the market, each of which is ideal for a different set of specific needs. As a rule, cloud platforms aren’t the best option for face recognition-based time and attendance management systems because they aren’t fault tolerant during Internet outages. You should also know that implementing a system using free libraries like OpenCV takes a long time, requires machine learning skills, and is difficult to scale. Taking these points into account, we compiled a list of ideal face technology software for you to try out.
Facial Recognition Solutions to Power Your Attendance Management System
Let’s start with CompreFace (github link). It is a promising face recognition solution that was just released in 2020. You can easily integrate CompreFace into any system without prior machine learning skills and use it for tracking employee productivity, controlling access to sensitive data, and identifying visitors. CompreFace features a UI panel with roles for access control and starts quickly with one docker command. Additionally, it uses one of the most popular high-accuracy face recognition methods. Best of all, it’s totally free.
Deep Vision AI detects and recognizes faces in your images and videos with AI-enabled technology. It provides the location of the detected faces and can perform facial matches to find target subjects. With Deep Vision’s facial analysis model, you can even estimate age and gender.
FaceFirst helps organizations detect real-time threats, impersonation attempts, and misuse of look-alike faces thanks to face recognition and automated video analytics. The software can detect faces accurately, even in poor lighting conditions. It searches a vast database at a rate of 350 million images per second. FaceFirst also features a highly configurable and flexible platform with a proprietary algorithm built with deep machine learning and neural networks.
Face++ is a powerful tool that uses face comparing and face searching to match people from your photos and videos with entries in the available database. The detected faces are stored in the FaceSet. Face_token is used as a unique ID for face detection under this system. It works in online and offline modes and has two licensing plans. Face++ features excellent accuracy, robust anti-spoofing techniques, and frequent model updating.
FaceX provides a face detection and face recognition web service that can be integrated with your apps with just a few lines of code. This online face recognition attendance system offers fast face processing, live face detection, a compact face features template, and face image quality determination all in one place.
Kairos is also worth your attention. Kairos has launched the Kairos Video Analytics Camera and Dashboard to help businesses get more customer data insights through customer identity and emotion detection. The Kairos Camera divides live videos into individual images and leverages facial recognition technology to determine customers’ identities. To ensure companies deliver a personalized experience to their customers, the device collects data about age and gender, customer status, and emotions.
Next up is Paravision, which is marketed for large enterprises. Paravision is one of the world’s most advanced face recognition platforms and is trained on an ever-expanding private global dataset of over 12 billion photos and videos. The software provides a comprehensive toolset for developing advanced face recognition solutions including face detection, face verification, face identification, and real-time streaming video. Paravision’s key features include face clustering, spoof detection, age estimation, gender detection, and behavior recognition capabilities.
The last program we’ll highlight is Trueface. Trueface is a face recognition company that applies advanced computer vision technology to camera footage and images to enable immediate decisions based on identified patterns. Trueface has developed a suite of SDKs and a dockerized container solution that harnesses the power of machine learning and artificial intelligence to transform your camera data into actionable intelligence. Trueface’s key features include face extraction, landmark detection, head pose estimation, and complete offline capabilities.
Why Face Recognition Software?
Facial recognition attendance monitoring systems are a great tool for businesses of all sizes to track their employees’ performance and monitor who comes in and out of the office, and they do all of this with greater efficiency than manual options. With facial recognition software, there’s no need to have personnel monitor systems all day long. An automated setup can report necessary information with high accuracy and reduce human error. Facial biometric tracking allows you to recognize strangers and track access to security information. It’s especially useful when you need to provide evidence that a person has entered your office. Face recognition technology can be easily integrated in your time and attendance management system without any additional tools. You’ll never need to worry about forgetting a password or recording employee hours on paper. As a result, your employees will have more time to concentrate on pressing issues instead of mundane processes.
Increased accuracy and efficiency are just some of the benefits to facial recognition-based attendance management options. We expect this area of the market to only grow in the near future as more and more organizations start to take advantage of machine learning and artificial intelligence solutions.