Published in Data Science and Engineering (DSE) Record 2024 Vol. 5 No. 1 pp. 47-61
Abstract
This research primarily aims to develop a system that uses machine learning technol-ogy to predict human height, weight, and body mass index (BMI) from a single full-body image. We proposes a novel method that utilizes the PiFuHD model to trans-form 2D images into 3D models, along with processes for feature extraction, feature selection, noise reduction of 3D point clouds, training and testing machine learning models. Data were collected from a survey of male and female Thai volunteers aged 18 to 65, without physical disabilities, for evaluating abilities of the models to pre-dict height, weight, and BMI. The effectiveness and accuracy of the machine learning methods were assessed using performance metrics such as mean absolute error (MAE). The results obtained from the testing set showed a MAE of 4.38 centimeters for height prediction, 8.56 kilograms for weight prediction, and 3.03 for body mass in-dex. This research opens avenues for researchers and interested parties to utilize the developed concepts and methods in creating applications or systems capable of effi-ciently predicting human height, weight, and body mass index from images.