Face analysis is essential for a large number of applications such as human-computer interaction or multimedia (e.g. content indexing and retrieval). Although many approaches are under investigation, performance under uncontrolled conditions is still not satisfactory. The variations that impact facial appearance (e.g. pose, expression, illumination, occlusion, motion blur) make it a difficult problem to solve.

This book describes the progress towards this goal, from a core building block – landmark detection – to the higher level of micro and macro expression recognition. Specifically, the book addresses the modeling of temporal information to coincide with the dynamic nature of the face. It also includes a benchmark of recent solutions along with details about the acquisition of a dataset for such tasks.

Romain Belmonte is a postdoctoral researcher in computer science at the University of Lille, France. His current research interests include computer vision, deep learning and human behavior analysis.

Benjamin Allaert is an associate professor at the IMT Nord Europe, the leading institute of technology in France. His research focuses on the development of digital simulations, deep learning and decision models to help humans better interact with their environment.