Reducing movement artifacts in whole body scanning
NRC '97 Proceedings of the International Conference on Recent Advances in 3-D Digital Imaging and Modeling
The space of human body shapes: reconstruction and parameterization from range scans
ACM SIGGRAPH 2003 Papers
IEEE Spectrum
Computer vision system for human anthropometric parameters estimation
WSEAS TRANSACTIONS on SYSTEMS
Human anthropometric parameters estimation using video based techniques
ICAI'09 Proceedings of the 10th WSEAS international conference on Automation & information
An intelligent system for customized clothing making
CIMMACS'08 Proceedings of the 7th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics
The development of an intelligent system for customized clothing making
Expert Systems with Applications: An International Journal
Automated body feature extraction from 2D images
Expert Systems with Applications: An International Journal
Constructing 3D human model from front and side images
Expert Systems with Applications: An International Journal
| Hi-index | 12.06 |
The development of three-dimensional (3D) whole body scanner opens opportunities for measuring human body more efficiently. While taking measurements from 3D scanning data, markers are usually placed on human body to facilitate landmarking and data collection. But the procedure of placing markers is very tedious and may involve human errors. The objective of this study is to develop an automated anthropometric data collection system to eliminate manual intervention. For 3D image analysis, the first step is to segment the body parts by analyzing the 2D silhouette. Then we use the approximate location estimates as the references for performing initial searches of the landmarks. Subsequently, four algorithms including silhouette analysis, minimum circumference determination, gray-scale detection, and human-body contour plots are developed to extract 12 landmarks and three characteristic lines on human body. Finally, from the results of automated landmarking, 104 anthropometric data can be obtained. To evaluate the validity and reliability of the automated anthropometric data collection system, 189 human subjects were scanned and the scanning data were processed by the system. The results demonstrated that the system was very effective and robust. Based on the newly developed system, many applications can be extended.