Metaverse Gait Authentication Dataset (MGAD)
收藏DataCite Commons2025-02-11 更新2025-04-16 收录
下载链接：
https://ieee-dataport.org/documents/metaverse-gait-authentication-dataset-mgad
下载链接
链接失效反馈官方服务：
资源简介：
The Metaverse Gait Authentication Dataset (MGAD) is a large-scale gait dataset designed for biometric authentication in virtual environments. It contains gait data from 5,000 simulated users, generated in Unity 3D and processed using OpenPose and MediaPipe to extract 16 key features, including stride length, step frequency, joint angles, ground reaction forces, and gait symmetry index. The dataset has undergone extensive preprocessing, feature engineering, and normalization to ensure high-quality, noise-free data suitable for machine learning applications. MGAD is a benchmark for evaluating gait-based authentication models in the Metaverse, enabling researchers to explore biometric security solutions in immersive environments.
提供机构：
IEEE DataPort
创建时间：
2025-02-11
