{"id":1882,"date":"2014-10-14T14:48:12","date_gmt":"2014-10-14T21:48:12","guid":{"rendered":"http:\/\/bestperformancegroup.com\/?page_id=1882"},"modified":"2014-10-14T16:58:22","modified_gmt":"2014-10-14T23:58:22","slug":"rigid-body-motion-tracking","status":"publish","type":"page","link":"http:\/\/bestperformancegroup.com\/?page_id=1882","title":{"rendered":"Rigid Body Motion Tracking"},"content":{"rendered":"

Photogrammetric reconstruction\u00a0is a process employed to recreate a 3D object from two or more 2D projections of the object of interest. \u00a0In optical motion tracking systems, these 2D projections are camera images from each camera used in the study. \u00a0In order to track both the location and orientation of a rigid body in space, at least three non-collinear markers are needed on the segment of interest. \u00a0These markers need to be captured simultaneously by at least two or more cameras.<\/p>\n

As was discussed in the rigid body mechanics<\/a> page, even though the human body skeleton is not truly rigid, it is typically modeled as a series of approximately rigid segments connected at joints. \u00a0Six parameters at a minimum are necessary to define the position of a rigid body in 3D, as there are 6 DOF for the rigid body. \u00a0The most common methods to define the rigid body in 3D space are:<\/p>\n

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  1. 6 parameters – a single 3D point with three coordinates (x, y, z) plus 3 orientation angles (\u03b1, \u03b2, \u03b3).<\/li>\n
  2. 7 parameters – two different 3D points (x1<\/sub>, y1<\/sub>, z1<\/sub>) and (x2<\/sub>, y2<\/sub>, z2<\/sub>) with 1 angle (\u03b1) between them.<\/li>\n
  3. 9 parameters – three different 3D points (x1<\/sub>, y1<\/sub>, z1<\/sub>), (x2<\/sub>, y2<\/sub>, z2<\/sub>), and (x3<\/sub>, y3<\/sub>, z3<\/sub>).<\/li>\n<\/ol>\n

    In optical motion capture studies, at least 3 non-collinear external markers are used per body segment to reconstruct the position and orientation of the body segment. Additional markers are often used per body segment in marker clusters<\/a> to increase the accuracy of the pose estimation through optimization routines to reduce the inherent error of the optical motion tracking systems as well as skin motion artifact<\/a> common with optical marker systems.<\/p>\n

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