Journal
COMPUTER VISION AND IMAGE UNDERSTANDING
Volume 162, Issue -, Pages 1-22Publisher
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.cviu.2017.08.008
Keywords
Face alignment; Active appearance model; Constrained local model; Cascaded regression; Deep convolutional neural networks
Funding
- National Science Foundation of China [61373060, 61672280]
- Qing Lan Project
- Funding of Jiangsu Innovation Program for Graduate Education [KYLX_0289]
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Over the last two decades, face alignment or localizing fiducial facial points on 2D images has received increasing attention owing to its comprehensive applications in automatic face analysis. However, such a task has proven extremely challenging in unconstrained environments due to many confounding factors, such as pose, occlusions, expression and illumination. While numerous techniques have been developed to address these challenges, this problem is still far away from being solved. In this survey, we present an up-to-date critical review of the existing literatures on face alignment, focusing on those methods addressing overall difficulties and challenges of this topic under uncontrolled conditions. Specifically, we categorize existing face alignment techniques, present detailed descriptions of the prominent algorithms within each category, and discuss their advantages and disadvantages. Furthermore, we organize special discussions on the practical aspects of face alignment in-the-wild, towards the development of a robust face alignment system. In addition, we show performance statistics of the state of the art, and conclude this paper with several promising directions for future research. (C) 2017 Elsevier Inc. All rights reserved.
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