Facial features detection and localization

Detection of facial landmarks and their feature points plays an important role in many facial image-related applications such as face recognition/verification, facial expression analysis, pose normalization, and 3D face reconstruction. Generally, detection of facial features is easy for persons; however, for machines it is not an easy task at all. The difficulty comes from high inter-personal variation (e.g., gender, race), intra-personal changes (e.g., pose, expression), and from acquisition conditions (e.g., lighting, image resolution). This chapter discusses basic concepts related to the problem of facial landmarks detection and overviews the successes and failures of exiting solutions. Also, it explores the difficulties that hinders the path of progress in the topic and the challenges involved in the adaptation of existing approaches to build successful systems that can be utilized in real-world facial images-related applications. Additionally, it discusses the performance evaluation metrics and the available benchmarking datasets. Finally, it suggests some possible future directions for research in the topic.