Anthropometric Measurements with 2D Images

Rumeysa Ashhan Ertürk, Mustafa Ersel Karnaşak
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Abstract

In this work, we designed and provided a proof-of-concept study for a novel system that takes several anthro-pometric measurements (bust, waist, and hip circumferences) simultaneously using only two (frontal and side) 2D images of a human subject. The system has two components: a specific camera setup with lasers and image analysis software. Towards this purpose, we compare body measurements of the proposed system and manual measurements on a limited number of subjects. For automatic measurements, we took one frontal and one side image from each subject. Body segmentation and pose estimation are applied to these images using pre-trained deep neural networks. Using the laser positions on the image, pixel sizes are estimated in terms of physical length (ie. centimeter). Using physical widths of the bust, waist, and hip in the images, their circumferences are estimated automatically. On three subjects, we obtained less than 10% measurement error. We concluded that anthropometric measurements could be obtained using a camera and laser setup. However, the number of subjects should be increased with a more precise laser to determine a better margin for measurement error.
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人体测量与二维图像
在这项工作中,我们设计并提供了一个新系统的概念验证研究,该系统仅使用人体受试者的两张(正面和侧面)2D图像同时进行几项人体测量(胸围、腰围和臀围)。该系统有两个组成部分:一个带有激光的特定摄像头和图像分析软件。为此,我们比较了拟议系统的身体测量和有限数量的受试者的人工测量。为了自动测量,我们为每个受试者拍摄了一张正面和一张侧面图像。使用预训练的深度神经网络对这些图像进行身体分割和姿态估计。利用激光在图像上的位置,根据物理长度(即。厘米)。使用图像中胸围、腰围和臀部的物理宽度,它们的周长被自动估计出来。在三个测试对象上,我们获得了小于10%的测量误差。我们的结论是,人体测量可以通过相机和激光装置来获得。然而,受试者的数量应该增加更精确的激光,以确定更好的测量误差范围。
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