Automatic Face Recognition Techniques using LBPH.
Nikhil Sontakke, Shweta Kulthe, Reshma Gaikwad, Tejas Ladkat · International journal of advance research and innovative ideas in education · 2018
Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. Due to social web portals and social networks, web users are motivated to share their pictures over the internet and that permit other users to tag and comment on the pictures. Many people share their posts, images on social portals, many are been labeled with appropriate names but many are not labeled, which becomes hard to understand the names for an unknown individual person. In this task, we need an efficient facial recognition (FR) system that can recognize everyone in the photo. However, more demanding privacy setting may limit the number of the photos publicly available to train the FR system. To deal with this dilemma, our mechanism attempts to utilize users’ private photos to design a personalized FR system specifically trained to differentiate possible photo co-owners without leaking their privacy. We also develop a distributed consensus-based method to reduce the computational complexity and protect the private training set. We show that our system is superior to other possible approaches in terms of recognition ratio and efficiency