Face Recognition using Deep Neural Network with "LivenessNet"
Samana Jafri, Satish Chawan, Afifa Khan · 2020
There is a continuous increase in the amount of population over the globe, and this, in turn, increases the number of complex datasets over a period. This necessitates improving artificial intelligence algorithms for better and accurate categorization of data. The most defining characteristic of the human body of the face. Every person’s face is unique, although have the same structure such as noise, eyes, lips, etc. but it can vary strikingly. It’s within this variance which lies the distinguishing characteristics that can be used to identify one person from another. Face recognition is a popular concept which is commonly used in surveillance cameras at public places for security purposes. The "Face Recognition using DNN with LivenessNet" presents a face recognition method based on deep neural networks for liveness. Any algorithm is considered to be efficient only if it is robust and accurate. It provides accurate results with face spoofing quickly and efficiently. The main advantage of using this technique is identifying the uniqueness in the datasets by capturing the real-time face data through different modes & jitter. Also providing accurate face recognition model which can be used for safety and security purpose.