Human Pose Estimation Using MediaPipe Pose and Optimization Method Based on a Humanoid Model

Seniors who live alone at home are at risk of falling and injuring themselves and, thus, may need a mobile robot that monitors and recognizes their poses automatically. Even though deep learning methods are actively evolving in this area, they have limitations in estimating poses that are absent or rare in training datasets. For a lightweight approach, an off-the-shelf 2D pose estimation method, a more sophisticated humanoid model, and a fast optimization method are combined to estimate joint angles for 3D pose estimation. As a novel idea, the depth ambiguity problem of 3D pose estimation is solved by adding a loss function deviation of the center of mass from the center of the supporting feet and penalty…

• NR
  National Research Foundation
• NR
  National Research Foundation of Korea

  Awards: NRF-2021R1A4A1022059, 2020R1A2C1014649, 2021R1A4A1022059
• MO
  Ministry of Science and ICT, South Korea

  Award: NRF-2021R1A4A1022059