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Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras.

Peyer KE, Morris M, Sellers WI - PeerJ (2015)

Bottom Line: The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines.The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments.The body segment parameters of six participants (four male and two female) are presented using the proposed method.

View Article: PubMed Central - HTML - PubMed

Affiliation: Faculty of Life Sciences, University of Manchester , Manchester , United Kingdom.

ABSTRACT
Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints.

No MeSH data available.


Related in: MedlinePlus

Methodology to estimate subject-specific body segment parameters using photogrammetry.(A) Photogrammetry; (B) Body segmentation; (C) Segment hulling; (D) Inertial parameter estimation.
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fig-12: Methodology to estimate subject-specific body segment parameters using photogrammetry.(A) Photogrammetry; (B) Body segmentation; (C) Segment hulling; (D) Inertial parameter estimation.

Mentions: However there are some specific issues with this technique that could to be improved for a more streamlined and potentially more accurate workflow (see Fig. 12, which summarises the steps involved in estimating body segment parameters using photogrammetry).


Subject-specific body segment parameter estimation using 3D photogrammetry with multiple cameras.

Peyer KE, Morris M, Sellers WI - PeerJ (2015)

Methodology to estimate subject-specific body segment parameters using photogrammetry.(A) Photogrammetry; (B) Body segmentation; (C) Segment hulling; (D) Inertial parameter estimation.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4359122&req=5

fig-12: Methodology to estimate subject-specific body segment parameters using photogrammetry.(A) Photogrammetry; (B) Body segmentation; (C) Segment hulling; (D) Inertial parameter estimation.
Mentions: However there are some specific issues with this technique that could to be improved for a more streamlined and potentially more accurate workflow (see Fig. 12, which summarises the steps involved in estimating body segment parameters using photogrammetry).

Bottom Line: The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines.The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments.The body segment parameters of six participants (four male and two female) are presented using the proposed method.

View Article: PubMed Central - HTML - PubMed

Affiliation: Faculty of Life Sciences, University of Manchester , Manchester , United Kingdom.

ABSTRACT
Inertial properties of body segments, such as mass, centre of mass or moments of inertia, are important parameters when studying movements of the human body. However, these quantities are not directly measurable. Current approaches include using regression models which have limited accuracy: geometric models with lengthy measuring procedures or acquiring and post-processing MRI scans of participants. We propose a geometric methodology based on 3D photogrammetry using multiple cameras to provide subject-specific body segment parameters while minimizing the interaction time with the participants. A low-cost body scanner was built using multiple cameras and 3D point cloud data generated using structure from motion photogrammetric reconstruction algorithms. The point cloud was manually separated into body segments, and convex hulling applied to each segment to produce the required geometric outlines. The accuracy of the method can be adjusted by choosing the number of subdivisions of the body segments. The body segment parameters of six participants (four male and two female) are presented using the proposed method. The multi-camera photogrammetric approach is expected to be particularly suited for studies including populations for which regression models are not available in literature and where other geometric techniques or MRI scanning are not applicable due to time or ethical constraints.

No MeSH data available.


Related in: MedlinePlus