• Sanyog Acharyya
• Sahaya Sakila

This project designs face recognition system for smart home/office security applications. The design is implemented using webcam and programmed using dlib and openCV. The connection between cam and computer can be both wired and wireless. The approach we are going to use for face recognition is fairly straight forward. The key here is to urge a deep neural network to supply a bunch of numbers that describe a face (known as face encodings). When you pass in two different images of the same person, the network should return similar outputs (i.e.closer numbers) for each pictures, whereas when you pass in images of two different people, the network should return very different outputs for the two images. This means that the neural network must be trained to mechanically establish totally different options of faces and calculate numbers supported that. The output of the neural network may be thought of as associate degree symbol for a selected person’s face, if you pass in different images of the same person, the output of the neural network are terribly similar/close, whereas if you pass in pictures of a distinct person, the output are terribly totally different. The additional feature here is that we are going to run this algorithm on database too, to make it more efficient than ever

open CV, dlib

"Advanced Face Recognition System using Dlib", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.539-543, April-2019, Available :http://www.jetir.org/papers/JETIR1904O89.pdf

"Advanced Face Recognition System using Dlib", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp539-543, April-2019, Available at : http://www.jetir.org/papers/JETIR1904O89.pdf