Human Age Estimation Based on Locality and Ordinal Information

• Published in: IEEE transactions on cybernetics Vol. 45; no. 11; pp. 2522 - 2534
• Main Authors: Li, Changsheng, Liu, Qingshan, Dong, Weishan, Zhu, Xiaobin, Liu, Jing, Lu, Hanqing
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.11.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adolescent; Adult; Age determination; Age estimation; Aged; Aging; Aging - physiology; Algorithms; Artificial Intelligence; Child; Child, Preschool; Correlation; Datasets; Discriminant analysis; Energy measurement; Estimation; Face; Face - physiology; Facial; feature selection; Humans; Image Processing, Computer-Assisted - methods; Infant; Infant, Newborn; Linear programming; local manifold structure; Manifolds; Middle Aged; Optimization; ordinal pattern; Preserves; semi-supervised learning; Young Adult; ordinal pattern; Age estimation; semi-supervised learning; feature selection; local manifold structure

In this paper, we propose a novel feature selection-based method for facial age estimation. The face aging is a typical temporal process, and facial images should have certain ordinal patterns in the aging feature space. From the geometrical perspective, a facial image can be usually seen as sampled...