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RGB-Depth motion sensing devices are designed to capture the human body in full size including its motion, whereas gaming versions of these devices are available at acceptable prices for end users. ReconstructMe SDK [1] was already reported as a powerful library which is capable to work with low-cost body scanning devices. Their combination allows the real-time 3D reconstruction of the body and the development of custom applications in C language [2]. Hence, the objective of the current work introduced in this paper is to evaluate the RGB-D sensor of Asus Xtion PRO Live [3] for application in the apparel industry in general and for automated body geometry detection and air gap evaluation in particular. Previous reports on low-cost sensors and systems [4], [5] have demonstrated that these devices already provide sufficient accuracy for certain measurements in the apparel industry. Due to their low price, they could be used in software applications designed for end users. For current evaluations, an upper torso was scanned both without clothing and with shirts of different sizes and colors. Measurement errors were evaluated and an algorithm for automatic gap evaluation based on generated meshes was developed.

Evaluation of the Accuracy and Suitability of Low-Cost RGB-D Sensor for Automated Air Gap Measuring in the Apparel Industry