A Survey on Facial Wrinkles Detection and Inpainting: Datasets, Methods, and Challenges
Moi Hoon Yap, Nazre Batool, Choon-Ching Ng, Mike Rogers, Kevin Walker
Abstract
Automatic facial wrinkles detection and inpainting algorithms have gained attention of researchers in cosmetics, forensics and computer vision. The majority of current inpainting algorithms was implemented on the whole face, despite the fact that only imperfections need inpainting. In general, the definition of an imperfection is sign of ageing, spot, scar and freckles. This paper focuses on wrinkles as it is an obvious sign of ageing. We survey the computer vision techniques in facial wrinkles localisation from detection to inpainting. We present a comprehensive literature review on benchmark datasets, automated wrinkles detection algorithms and facial inpainting algorithms. Due to limited study on wrinkle inpainting, we inpaint the wrinkle regions using three state-of-the-art inpainting algorithms, namely flood-fill, Coherence Sensitivity Hashing and exemplar-based method. To assess the realism of inpainting results, we present the original and inpainted images to 40 participants, where they provide rating on the realism scale and age group of each image. The result shows that flood-fill method preserved the realism but there was no significant difference in age prediction. Finally, we conclude the paper by proposing some future directions to advance this field.