Human Motion Tracking with Less Constraint of Initial Posture from a Single RGB-D Sensor

• Published in: Sensors (Basel, Switzerland) Vol. 21; no. 9; p. 3029
• Main Authors: Liu, Chen, Wang, Anna, Bu, Chunguang, Wang, Wenhui, Sun, Haijing
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 26.04.2021; MDPI
• Subjects: 4D reconstruction; Deformation; Efficiency; Geometry; Human body; Human motion; human motion capture; Humans; Mesh generation; Methods; Motion; Motion capture; Neural networks; Posture; Reproducibility of Results; RGB-D sensor; Semantics; Sensors; Warping; RGB-D sensor; human motion capture; 4D reconstruction
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s21093029

High-quality and complete human motion 4D reconstruction is of great significance for immersive VR and even human operation. However, it has inevitable self-scanning constraints, and tracking under monocular settings also has strict restrictions. In this paper, we propose a human motion capture system combined with human priors and performance capture that only uses a single RGB-D sensor. To break the self-scanning constraint, we generated a complete mesh only using the front view input to initialize the geometric capture. In order to construct a correct warping field, most previous methods initialize their systems in a strict way. To maintain high fidelity while increasing the easiness of the system, we updated the model while capturing motion. Additionally, we blended in human priors in order to improve the reliability of model warping. Extensive experiments demonstrated that our method can be used more comfortably while maintaining credible geometric warping and remaining free of self-scanning constraints.