Survey on Face Detection & Recognition Techniques

Abstract

Face detection is an extensively  investigated subject in the realm of computer vision and holds considerable significance in diverse applications, encompassing  human-computer interfaces, video surveillance, security access control systems, video surveillance, and image database management. Numerous face detection methods have already been devised, like Viola-Jones, RCNN, SSD among others. This paper discusses some additions that have been done on the existing models and systems in a bid to produce better outputs, using the standard datasets like WIDERFACE, FDDB etc. The face detection and recognition techniques discussed here employ the following approaches: (i) Mask R-CNN (ii) MTCNN, (iii) Local Binary Pattern Histogram (LBPH), (iv) PCA with Eigenfaces (iv) Weighted Kernel PCA, and (v) VGG architectures such as Siamese-VGG.