Analysis of Kinect-Based Human Motion Capture Accuracy Using Skeletal Cosine Similarity Metrics.

ABSTRACT: Kinect, with its intrinsic and accessible human motion capture capabilities, found widespread application in real-world scenarios such as rehabilitation therapy and robot control. Consequently, a thorough analysis of its previously under-examined motion capture accuracy is of paramount importance to mitigate the risks potentially arising from recognition errors in practical applications. This study employs a high-precision, marker-based motion capture system to generate ground truth human pose data, enabling an evaluation of Azure Kinect's performance across a spectrum of tasks, which include both static postures and dynamic movement behaviors. Specifically, the cosine similarity for skeletal representation is employed to assess pose estimation accuracy from an application-centric perspect

SUBMITTER: Jia W 

PROVIDER: S-EPMC11860043 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature