Skurowski, P.; Pawlyta, M. Detection and Classification of Artifact Distortions in Optical Motion Capture Sequences. Sensors2022, 22, 4076.
Skurowski, P.; Pawlyta, M. Detection and Classification of Artifact Distortions in Optical Motion Capture Sequences. Sensors 2022, 22, 4076.
Skurowski, P.; Pawlyta, M. Detection and Classification of Artifact Distortions in Optical Motion Capture Sequences. Sensors2022, 22, 4076.
Skurowski, P.; Pawlyta, M. Detection and Classification of Artifact Distortions in Optical Motion Capture Sequences. Sensors 2022, 22, 4076.
Abstract
Optical motion capture systems are prone to the errors connected with markers recognition – occlusion, leaving the scene or mislabelling – all these errors are then corrected in the software, but still, the process is not perfect, resulting in artifact distortions. In the article, we examine four existing types of artifacts, then propose the method for detection and classification of the distortions. The algorithm is based on the derivative analysis, low-pass filtering, mathematical morphology and loose predictor. The tests involved multiple simulations using synthetically distorted sequences, comparison of performance to the human operators on real life data and applicability analysis for the distortion removal.
Computer Science and Mathematics, Hardware and Architecture
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
