title: Face morphology: Can it tell us something about body weight and fat?
abstract: This paper proposes a method for an automatic extraction of geometric features, related to weight parameters, from 3D facial data acquired with low-cost depth scanners. The novelty of the method relies both on the processing of the 3D facial data and on the definition of the geometric features which are conceptually simple, robust against noise and pose estimation errors, computationally efficient, invariant with respect to rotation, translation, and scale changes. Experimental results show that these measurements are highly correlated with weight, BMI, and neck circumference, and well correlated with waist and hip circumference, which are markers of central obesity. Therefore the proposed method strongly supports the development of interactive, non obtrusive systems able to provide a support for the detection of weight-related problems.
authors: Institute of Information Science and Technologies, National Research Council, Pisa, Italy. Electronic address: maria.antonietta.pascali@isti.cnr.it.
authors: M A
authors: MA
authors: Pascali
authors: Institute of Information Science and Technologies, National Research Council, Pisa, Italy.
authors: D
authors: D
authors: Giorgi
authors: Institute of Clinical Physiology, National Research Council, Pisa, Italy.
authors: L
authors: L
authors: Bastiani
authors: Institute of Clinical Physiology, National Research Council, Pisa, Italy.
authors: E
authors: E
authors: Buzzigoli
authors: Computer Vision and Machine Learning Research Group, School of Engineering, College of Science and Technology, University of Central Lancashire, Preston, UK.
authors: P
authors: P
authors: Henriquez
authors: Computer Vision and Machine Learning Research Group, School of Engineering, College of Science and Technology, University of Central Lancashire, Preston, UK.
authors: B J
authors: BJ
authors: Matuszewski
authors: Institute of Clinical Physiology, National Research Council, Pisa, Italy.
authors: M-A
authors: MA
authors: Morales
authors: Institute of Information Science and Technologies, National Research Council, Pisa, Italy.
authors: S
authors: S
authors: Colantonio
mesh_terms: D000273:Adipose Tissue / Q000502:physiology*; D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015992:Body Mass Index; D001835:Body Weight / Q000502:physiology*; D005145:Face / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional; D008297:Male; D008875:Middle Aged; D010780:Photogrammetry; D055815:Young Adult
keywords: 3D scanning and reconstruction; BMI; Facial morphology; Structural equation model; Weight and fat-related parameters