An Effective Model for Intergrated Face Detection and Recognition

EasyChair Preprint 2183

Abstract

Facial recognition, an attractive field in computer-based application, has been one of the most widely research and challenging areas in computer vision and machine learning. The innovation of new face authentication technologies is a controversal topic to build much effective and robust face recognition algorithms. In this work, an effective, fast and reliable model is proposed based on combining traditional algorithms such as HOG, SVM and the modern ones such as ResNet50, Facial Landmark 68 for face recognition and emotion detection. Tests on different databases of large number of samples, various environmental conditions and facial expressions are presented with high recognition results.

Keyphrases: Histogram of Oriented Gradients (HOG), Open Face framework, Residual Neural Network (ResNet), Support Vector Machine (SVM)

@booklet{EasyChair:2183,
  author    = {Huy Quang Tran and Nhat Tien Le and Quang Luong Nguyen and Dat Tan La and Thu Thi Anh Nguyen},
  title     = {An Effective Model for Intergrated Face Detection and Recognition},
  howpublished = {EasyChair Preprint 2183},
  year      = {EasyChair, 2019}}