Face To BMI: Predicting Body Mass Index Using Neural Networks
G Lavanya, M Kushal, G. Gayathri, M. Revanth
Body Mass Index (BMI), a vital health metric indicating weight relative to height, classifies individuals
as underweight, normal weight, overweight, or obese, guiding early interventions for health risks, but
traditional methods relying on height and weight measurements are labor-intensive, making automated
BMI assessment a scalable and efficient alternative for health analysis and decision-making; leveraging
facial features, which reveal correlations between face geometry and BMI, we employed large-scale pretrained models like EfficientNet-B7, Swin-Transfomer, and ResNeSt- 101, trained on diverse datasets
such as the Illinois DOC, Height-weight-BMI dataset with Celebrity Faces, to enhance prediction
accuracy, scalability, and applications in health monitoring, insurance, and policymaking, thereby
enabling informed societal and individual health decisions.
