A Review on Comparative Analysis of Face Detection Algorithms

Abstract

Facial recognition plays a vital role in computer vision applications. Several face detection algorithms have been developed over time to accurately detect human faces in images and videos. In this review paper, we present an overview and comparative analysis of traditional face detection algorithms such as Haar cascades and Viola-Jones, as well as newer methods such as SIFT, SURF, ORB, and LBP. We discuss the key features, benefits, and limitations of each algorithm and provide a detailed comparison table for ease of reference. Our analysis shows that each algorithm has strengths and weaknesses, and the choice of algorithm is dependent on the application's specific requirements. We conclude by highlighting the need for more robust and efficient algorithms. Overall, this review paper provides a comprehensive guide for face detection researchers and practitioners.