@inproceedings{trivedi2021height,
author = {Trivedi, Anusua and Jain, Mohit and Kumar Gupta, Nikhil and Hinsche, Markus and Singh, Prashant and Matiaschek, Markus and Behrens, Tristan and Militeri, Mirco and Birge, Cameron and Kaushik, Shivangi and Mohapatra, Archisman and Chatterjee, Rita and Dodhia, Rahul and Lavista Ferres, Juan and Lavista Ferres, Juan M.},
title = {Height Estimation of Children under Five Years using Depth Images.},
booktitle = {IEEE International Engineering in Medicine and Biology Conference (EMBC)},
year = {2021},
month = {May},
abstract = {Malnutrition is a global health crisis and is the leading cause of death among children under five. Detecting malnutrition requires anthropometric measurements of weight, height, and middle-upper arm circumference. However, measuring them accurately is a challenge, especially in the global south, due to limited resources. In this work, we propose a CNN-based approach to estimate the height of standing children under five years from depth images collected using a smart-phone. According to the SMART Methodology Manual [5], the acceptable accuracy for height is less than 1.4 cm. On training our deep learning model on 87131 depth images, our model achieved an average mean absolute error of 1.64% on 57064 test images. For 70.3% test images, we estimated height accurately within the acceptable 1.4 cm range. Thus, our proposed solution can accurately detect stunting (low height-for-age) in standing children below five years of age.},
publisher = {IEEE},
url = {http://approjects.co.za/?big=en-us/research/publication/height-estimation-of-children-under-five-years-using-depth-images-2/},
}