This paper presents methods and algorithms to automatically segment and measure the human body.
In the segmentation procedure, two different methods are designed to find the crotch point for the situation of non‐contacted thigh and contacted thigh, respectively. Three different methods: minimum distance algorithm, minimum inclination angle algorithm, and directional neighbor identification algorithm are introduced to search the branching points or triangle. In the body measurement procedure, a pre‐sorted circling method is designed for circumference measurement, and the basic principle of landmark acquisition has been discussed. These techniques are validated via testing over different type of scanned model.
The results of automatic segmentation and body measurement have verified that our methods are efficient and versatile in processing different type of scanned body.
The accurate and automatic locating of wrist, ankle and knees contour can be more difficult than it appears to be.
The main usage of scanned body in our research is for 3D garment try‐on.
This paper introduces the methods for crotch identification, and the methods including minimum distance algorithm, minimum inclination angle algorithm, and directional neighbor identification algorithm for human body segmentation. It also explains the fundamental measuring techniques, and outlines the results of using these techniques in segmentation and measurement.
Zhong, Y. and Xu, B. (2006), "Automatic segmenting and measurement on scanned human body", International Journal of Clothing Science and Technology, Vol. 18 No. 1, pp. 19-30. https://doi.org/10.1108/09556220610637486Download as .RIS
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