Affiliations: [a] School of Computing Science and Engineering, VIT University, Vellore, India | [b] Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA | [c] Department of Pediatrics, University of Cincinnati, Cincinnati, OH, USA | [d] Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Cincinnati, OH, USA | [e] Department of Electrical Engineering and Computer Science, University of Cincinnati, Cincinnati, OH, USA
Correspondence:
[*]
Corresponding author: V.B. Surya Prasath, Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA. E-mail: surya.prasath@cchmc.org.
Abstract: Body mass index (BMI) is used widely as an indicator in general health. Determination of BMI using non-intrusive measurements are of interest and recent advancements in the availability of digital imaging sensors have paved the way for performing quick and automatic measurements. In this work, we consider automatic computation of BMI using correlation features from face images. We show that using face detection based facial fiducial points analysis provides good BMI prediction. Experimental results on comparing the correlation coefficients of facial ratios along with the colour feature has higher significance in BMI of a person.
Keywords: Body mass index (BMI), facial features, correlation coefficient
