Facial Recognition System
Highly Accurate Real-Time Facial Recognition Solution
At Folio3 we believe in innovation and as our appetite for excellence increases, so does our product catalog. Since crafting solutions through intense research is one of our forte, we took on a project for developing a proprietary product in the facial recognition vertical.
The Folio3 Solution
Our company Folio3 wanted to build a solution that offered a highly accurate facial recognition system which provides real time results based on Histogram of Oriented Gradients (HOG) and Convolutional Neural Network (CNN). Utilizing the dLib for face recognition and object oriented detection we were able to accurately showcase results in real-time.
Using the human face as a key to security, biometric face recognition technology has received significant attention over the past few years due to the potential it offers to a wide variety of applications in both law enforcement and non-law enforcement verticals.
As compared to other biometric systems that use fingerprint/palm-print and iris detection, face recognition offers distinct advantages due to its non-contact process. Face images can be captured from a distance without touching the person being identified and the identification does not require interacting with the person.
Key Features Of Our Solution
Specific faces can be registered in advance to alert the system or authorities when they are detected. For instance, the faces of repeat shoplifters and wanted criminals can be registered easily in the facial recognition system from data recorded in the past.
Face images can be used to perform searches, this would help in directly locating a specific person or individuals in the database as the system matches the specimen’s face through images in real time.
Information can also be shared between facial recognition systems by importing generic photo data in the JPEG format. The generic photo data can then be saved into multiple databases and used as archive or for real-time face search.
The system can also notify the users about specific face images through pop-up notifications proactively to help in identifying a specific individual. Alarms can notify the operator by displaying pop-ups on the screen, emitting warning sounds, or flashing the camera on the map.
Thanks to the advanced facial recognition system developed by Folio3’s expert team, organizations can now leverage the information for a proactive approach in a more controlled environment to systematically monitor and manage security processes by identifying specific human faces.
Technologies used: CNN, HOG, DLIB and OpenCV