Calibration effects on markerless system performance
Abstract
The motion capture techniques based on markers have been used worldwide for gait analysis for years. However, despite the accuracy, this is a costly method that needs specialized equipment and personnel. That’s the reason why, nowadays, new low-cost methods such as the markerless techniques based on human pose estimation have been developed. The calibration stage in motion capture systems is an important procedure that clearly impacts on the system performance. However, it is not fully validated how the results are affected by variations in the calibration procedures. This work proposes to evaluate 2 different spatial configurations of the acquisition devices modifying their height (H1, highest and H2, lowest) and different calibration procedures (intrinsics and extrinsics parameters) in a markerless system based on 4 smartphones IPhone SE. To evaluate the impact of intrinsics parameters, the distance between calibration pattern and camera (DPC); and the number of registered frames (\#frames) are modified. Three different calibration patterns (extrinsics calibration) were evaluated to quantify the effect on markerless system performance. The final results of the trajectory of the markers are compared to the gold standard method, 8 VICON Bonita cameras, data which is captured simultaneously. Comparisons are realized considering two metrics widely used in bibliography (MPJPE and PCK). The results show that H1 configuration performs slightly better than H2. Regarding extrinsic calibration, patterns that consider a volume more than a surface are better for both configurations. About the intrinsic calibration, the best performance is given by the minimum DPC with pattern 2, with a negligible influence of \#frames. Respecting PCK performance for different thresholds, the results are worse (higher $\tau^{*}$ values) for $H 2$ than for $H 1$ in most of the markers. Comparing both methods, the most affected direction is the transversal while the vertical and anteroposterior were similar to each other.
Fields of Study & Subjects
Analog and Mixed-Signal Circuit Design
Distributed Sensor Networks and Detection Algorithms
Target Tracking and Data Fusion in Sensor Networks
Publication details
- Journal / source
- 2026 IEEE Medical Measurements & Applications (MeMeA)
- Publisher
- IEEE
- Pages
- 1–6
- Publication date
- 7 April 2026