| Title |
Calibration-free shoulder kinematics using single and dual asynchronous RGB-D cameras |
| Authors |
Abromavičius, Vytautas ; Griškevičius, Julius ; Matuzevičius, Dalius ; Maknickas, Algirdas ; Plonis, Darius ; Maskeliūnas, Rytis |
| DOI |
10.1109/ACCESS.2026.3659738 |
| Full Text |
|
| Is Part of |
IEEE Access.. Piscataway, NJ : IEEE. 2026, vol. 14, p. 17381-17394.. ISSN 2169-3536 |
| Keywords [eng] |
computer vision ; human pose estimation ; motion capture ; pose estimation ; single person pose estimation |
| Abstract [eng] |
This study experimentally evaluates whether shoulder joint kinematics can be accurately reconstructed using calibration free asynchronous RGB-D cameras under rehabilitation relevant conditions. We present a markerless framework that jointly learns temporal alignment, geometric consistency, and pose reconstruction using continuous-time modeling based on Neural Ordinary Differential Equations and implicit representations, eliminating the need for hardware synchronization or manual camera calibration. The system was validated in a controlled laboratory setting against a BTS Smart-DX optical motion capture reference during five clinically relevant shoulder movements. Performance was assessed for single- and dual-camera configurations. The dual-camera setup achieved a mean joint position error of 15.4 ± 2.8 mm with low temporal jitter (5.9 ± 0.7 mm), while the single-camera configuration showed reduced accuracy and higher sensitivity to occlusion. The results demonstrate that calibration-free asynchronous RGB-D systems can provide feasible shoulder kinematics, with a clear accuracy–complexity trade-off between single-and dual-camera deployments. |
| Published |
Piscataway, NJ : IEEE |
| Type |
Journal article |
| Language |
English |
| Publication date |
2026 |
| CC license |
|