Conference Agenda

Accurate estimation of joint centres from skin-mounted marker trajectories is a prerequisite for anatomically plausible virtual human animation in biomechanics, ergonomics and computer graphics. Marker-based stereophotogrammetric systems provide high-resolution kinematic data, yet the inherent offset between epidermal markers and the underlying skeletal structures imposes a fundamental limitation on direct retargeting approaches. This paper presents a ge-ometric reconstruction framework that infers joint centre locations and skeletal segment axes from Vicon optical motion-capture data without assuming a one-to-one correspondence between external landmarks and internal anatomical nodes. The method employs a three-sphere tangent-line construction applied to selected marker subsets to estimate the proximal and distal articulations of each rigid segment. Applied to the femoral segment, the algorithm was validated on three kinematically distinct motor tasks—straight walking, vertical jumping and running—obtained from exhaustive combinatorial sampling of all three-frame subsets. The median femoral length remained remarkably consistent across tasks (0.491, 0.486 and 0.471 m; cross-task range 21 mm), and the optimised sphere radii were anatomically coherent with published marker-to-bone distances. A sensitivity analysis identified the pelvic-midpoint radius as the dominant source of length variability (|r| > 0.95), while outlier triads were traced to geometrically degenerate frame selections with insufficient postural diversity. The proposed framework is directly applicable to subject-specific biomechanical analyses, musculoskeletal modelling and movement simulations where accurate, non-invasive joint centre estimation from surface markers is required.