A review of image-based automatic facial landmark identification techniques

• Published in: EURASIP journal on image and video processing 2018-09, Vol.2018 (1), p.1-23, Article 86
• Main Authors: Johnston, Benjamin, Chazal, Philip de
• Format: Article
• Language: English
• Subjects: Artificial neural networks; Biometrics; Computer vision; Engineering; Face; Face recognition; Image Processing and Computer Vision; Landmarking; Landmarks; Machine learning; Neural networks; Pattern Recognition; Registration; Review; Signal,Image and Speech Processing; Vision
• ISSN: 1687-5281; 1687-5176; 1687-5281
• DOI: 10.1186/s13640-018-0324-4

The accurate identification of landmarks within facial images is an important step in the completion of a number of higher-order computer vision tasks such as facial recognition and facial expression analysis. While being an intuitive and simple task for human vision, it has taken decades of research, an increase in the availability of quality data sets, and a dramatic improvement in computational processing power to achieve near-human accuracy in landmark localisation. The intent of this paper is to provide a review of the current facial landmarking literature, outlining the significant progress that has been made in the field from classical generative methods to more modern techniques such as sophisticated deep neural network architectures. This review considers a generalised facial landmarking problem and provides experimental examples for each stage in the process, reporting repeatable benchmarks across a number of publicly available datasets and linking the results of these examples to the recently reported performance in the literature.