Advances in Face Image Analysis: Theory and applications

Advances in Face Image Analysis: Theory and applications describes several approaches to facial image analysis and recognition. Eleven chapters cover advances in computer vision and pattern recognition methods used to analyze facial data. The topics addressed in this book include automatic face detection, 3D face model fitting, robust face recognition, facial expression recognition, face image data embedding, model-less 3D face pose estimation and image-based age estimation. The chapters are also written by experts from a different research groups. Readers will, therefore, have access to contemporary knowledge on facial recognition with some diverse perspectives offered for individual techniques. The book is a useful resource for a to a wide audience such as i) researchers and professionals working in the field of face image analysis, ii) the entire pattern recognition community interested in processing and extracting features from raw face images, and iii) technical experts as well as postgraduate computer science students interested in cutting edge concepts of facial image recognition.

Table of Contents

Chapter 1 Facial Expression Classification Based on Convolutional Neural Networks
Chapter 2 Sparsity Preserving Projection Based Constrained Graph Embedding and Its Application to Face Recognition
Chapter 3 Face Recognition Using Exponential Local Discriminant Embedding
Chapter 4 Adaptive Locality Preserving Projections for Face Recognition
Chapter 5 Face Recognition Using 3D Face Rectification
Chapter 6 3D Face Recognition
Chapter 7 Model-Less 3D Face Pose Estimation
Chapter 8 Efficient Deformable 3D Face Model Fitting to Monocular Images
Chapter 9 Face Detection Using the Theory of Evidence
Chapter 10 Fuzzy Discriminant Analysis: Considering the Fuzziness in Facial Age Feature Extraction
Chapter 11 Facial Image-Based Age Estimation