Improved structured light 3D scanner with application to anthropometric parameter estimation
► New light pattern is more accurate and robust compared to standard light pattern. ► New light pattern volumetric measurements are comparable to immersion method result. ► Proposed 3D scanner can be used for accurate anthropometric parameter estimation. Obtaining accurate anthropometric body segmen...
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Published in | Measurement : journal of the International Measurement Confederation Vol. 46; no. 1; pp. 716 - 726 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.01.2013
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Subjects | |
Online Access | Get full text |
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Summary: | ► New light pattern is more accurate and robust compared to standard light pattern. ► New light pattern volumetric measurements are comparable to immersion method result. ► Proposed 3D scanner can be used for accurate anthropometric parameter estimation.
Obtaining accurate anthropometric body segment parameters in a fast and reliable manner is an essential step in biomechanical analysis of human motion. With advance of computer vision, and reduction in cost of electronic components, building a customized computer-vision based measurement device becomes possible. In the paper a novel structured light pattern for 3D structured light scanner is proposed. During development, accuracy and robustness of the proposed system were tested on artificial objects with known surface configurations, after which measurements were performed on human subjects. Simultaneous measurements with standard structured light pattern were achieved and obtained results compared. Volumetric parameters of both artificial object and human body segment obtained by 3D scanning were compared to the immersion method and were found to be in a good agreement and were used for segment mass estimation. Obtained results are presented and analyzed, and conclusions about system performance with possible improvements are discussed. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 ObjectType-Article-1 ObjectType-Feature-2 |
ISSN: | 0263-2241 1873-412X |
DOI: | 10.1016/j.measurement.2012.09.010 |