Introductory Chapter: Face Recognition - Overview, Dimensionality Reduction, and Evaluation Methods
S. Ramakrishnan · InTech eBooks · 2016
Face recognition is one of most popular and powerful applications in modern computing industries [1][2][3][4].It has found applications ranging from person identification (surveillance) [5] to emotion identification (human-machine interaction) [6].Over the past few decades, researchers in field of computers and electrical and electronics engineering have worked continuously to improve the performances of the face recognition systems.In-spite of these continuous efforts, there are still a plenty of scope for the new and additional research in the field of face recognition.This is due to the popularization of light-weight computing devices, increased customer expectations, and business competitions.Now the world best cameras in terms of resolution are available in smart phones at affordable price, and CCD cameras are found even in houses and almost in all commercial, business, and office environments including small-sized enterprises.Amount of face images being captured keep on increasing, and recognition of faces among these huge databases makes the task further challenging.One of most the important subtopics in face recognition is dimensionality reduction [1], because storing and processing of these high-resolution face images from huge database using light-weight devices require dimensionality reduction.Several different face recognition systems, including hardware (cameras, memory disk, and processors) and software, are available in the market.These face recognition systems provide better performance in one aspect and lack in other aspect.Comprehensive evaluation the performances of face recognition systems is the need of the hour.Keeping these factors in mind, this book on "face recognition" is focusing on dimensionality reduction and evaluation methods.This book is brief but comprehensive.Other than this introductory chapter, this book has four more chapters, two chapters for dimensionality reduction and one for an overview of the face recognition systems and evaluation methods.