Distortion Correction for 3D Scan of Trunk Swaying Human Body Segments

We propose a method for acquiring a 3D shape of human body segments accurately. Using a light stripe triangulation range finder, we can acquire accurate 3D shape of a motionless object in dozens of seconds. If the object moves during the scanning, the acquired shape would be distorted. Naturally, hu...

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Veröffentlicht in:ELCVIA Electronic Letters on Computer Vision and Image Analysis Jg. 7; H. 4; S. 51 - 61
Hauptverfasser: Funatomi, Takuya, Iiyama, Masaaki, Kakusho, Koh, Minoh, Michihiko
Format: Journal Article
Sprache:Englisch
Japanisch
Veröffentlicht: Centre de Visió per Computador 15.04.2009
Universitat Autonoma de Barcelona
Computer Vision Center Press
Schlagworte:
3D Reconstruction
Anthropometry
Antropometria
Antropometría
Computer engineering. Computer hardware
Electronic computers. Computer science
Human Body Modeling
Light Stripe Triangulation
Modeling Cos Humà
Modeling Cuerpo Humano
QA75.5-76.95
Reconstrucció en 3D
Reconstrucción en 3D
TK7885-7895
Tronc d'un vaivé
Tronco de un vaivén
Trunk Swaying
ISSN:1577-5097, 1577-5097
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Zusammenfassung:We propose a method for acquiring a 3D shape of human body segments accurately. Using a light stripe triangulation range finder, we can acquire accurate 3D shape of a motionless object in dozens of seconds. If the object moves during the scanning, the acquired shape would be distorted. Naturally, humans move slightly for making balance while standing even if the subject makes an effort to stay still for avoiding the distortion in acquired shape. Our method corrects the distortion based on measured subject’s motion during the scanning. Experimental results show the accuracy of the proposed method. Trunk swaying degrades the accuracy of the light stripe triangulation from 1mm to 10mm. We can keep the accuracy of as good as 2mm by applying our method.
Bibliographie:1577-5097
https://raco.cat/index.php/ELCVIA/article/view/132011/181856
ELCVIA: electronic letters on computer vision and image analysis; 2008: Vol.: 7 Núm.: 4 Special Issue on Human Motion Analysis and Recognition; 51-61
ISSN:1577-5097
1577-5097
DOI:10.5565/rev/elcvia.251