Novel framework: face feature selection algorithm for neonatal facial and related attributes recognition

Muhammad Awais, Chen Chen (Corresponding author), Xi Long, B. Yin, Anum Nawaz, Saadullah Farooq Abbasi, Saeed Akbarzadeh, Linkai Tao, Chunmei Lu, Laishuan Wang, Ronald M. Aarts, Wei Chen (Corresponding author)

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
19 Downloads (Pure)

Abstract

In recent times, with the advancement of digital imaging, automatic facial recognition has been intensively studied for adults, while less for neonates. Due to the miniature facial structure and facial attributes, newborn facial recognition remains a challenging area. In this paper, an automatic video-based Neonatal Face Attributes Recognition (NFAR) approach in a hierarchical framework is proposed by coalescing the intensity-based method, pose estimation, and novel dedicated neonatal Face Feature Selection (FFS) algorithm. The intensity-based method is used for face detection, followed by the facial pose estimation algorithm and FFS are dedicated to neonatal pose and face feature recognition, respectively. In this study, video-data of 19 neonates’ were collected from the Children’s Hospital affiliated to Fudan University, Shanghai, to evaluate the proposed NFAR approach. The results show promising performance to detect the neonatal face, pose estimation (-450, 450), and facial features (nose, mouth, and eyes) recognition. The NFAR approach exhibits a sensitivity, accuracy, and specificity of 98.7%, 98.5%, and, 95.7% respectively, for the newborn babies at the frontal (00) facial region. The neonatal face and its attributes recognition can be expected to detect neonate’s medical abnormalities unobtrusively by examining the variation in newborn facial texture pattern.
Original languageEnglish
Article number9044721
Pages (from-to)59100-59113
Number of pages14
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 23 Mar 2020

Keywords

  • Neonatal face detection
  • face neonatal attributes recognition (NFAR)
  • facial feature selection (FFS)
  • neonatal pose estimation
  • video electroencephalogram (VEEG)

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