Development of a vision based anthropometric estimation system
| dc.contributor.author | Gan, Xu Yang | |
| dc.date.accessioned | 2021-02-23T03:48:07Z | |
| dc.date.available | 2021-02-23T03:48:07Z | |
| dc.date.issued | 2019-06 | |
| dc.description.abstract | Anthropometry can be defined as the science of dimensional measurement of the size and proportions of the human body, whether living or dead. Anthropometric measurement is used in a lot of fields such as medical, forensics and clothing. The modern anthropometry techniques are expensive and takes up a lot of space while traditional anthropometry techniques are slow and susceptible to human error. Traditional anthropometry method also poses a risk of sexual harassment during measurement while modern anthropometry method using X-ray might cause harm to human health and environment due to radiation. Hence, there is a need for the development of a vision-based estimation system that is safe, cheap, fast, accurate and portable. The study in this project proposes a noble way of using Raspberry 3B+ with Logitech C310 camera to perform estimation of chest, waist, hip circumference and body height through 2D images. The system works by implementing Pixel Density Method, HSV thresholding method, OpenPose deep neural network, bounding box method, pixel counting method and Ramanujan’s ellipse circumference approximation method to achieve the objectives of this study. The percentage error between the estimated result and the measured result of chest, waist, hip circumference and body height are only 2.11%, 4.66%, 4.31% and 1.74%. In conclusion, a vision based anthropometric estimation system is successfully developed with high accuracy using all the proposed methods. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/11472 | |
| dc.language.iso | en | en_US |
| dc.title | Development of a vision based anthropometric estimation system | en_US |
| dc.type | Other | en_US |
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