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This paper aims to present an unmarked method including entire two-dimensional (2D) and three-dimensional (3D) methods to recover absolute 3D humanoid robot poses from multiview images.

The method consists of two separate steps: estimating the 2D poses in multiview images and recovering the 3D poses from the multiview 2D heatmaps. The 2D one is conducted by High-Resolution Net with Epipolar (HRNet-Epipolar), and the Conditional Random Fields Humanoid Robot Pictorial Structure Model (CRF Robot Model) is proposed to recover 3D poses.

The performance of the algorithm is validated by experiments developed on data sets captured by four RGB cameras in Qualisys system. It illustrates that the algorithm has higher Mean Per Joint Position Error than Direct Linear Transformation and Recursive Pictorial Structure Model algorithms when estimating 14 joints of the humanoid robot.

A new unmarked method is proposed for 3D humanoid robot pose estimation. Experimental results show enhanced absolute accuracy, which holds important theoretical significance and application value for humanoid robot pose estimation and motion performance testing.

The purpose of the study was to assess the relationship between child sexual abuse (CSA) and posttraumatic stress disorder (PTSD) in female inmates in China. A total of 471 participants were assessed for CSA, personality traits, coping strategies, and frequency of lifetime PTSD. Results demonstrated that CSA and negative coping were predictive factors for lifetime PTSD among female inmates after personality traits were controlled. The findings suggest that CSA is one potential factor contributing to lifetime PTSD among female inmates. The importance of screening for CSA among female inmates was highly emphasized. Early intervention and prevention programmes based on coping skills may be useful to forestall the development of chronic PTSD in female inmates.