The invention discloses an
occlusion state 3D
human body posture
estimation method based on multistage optimization. According to the method, a plurality of synchronously calibrated cameras are used for acquiring RGB images, and a plurality of data enhancement strategies including
random rotation, horizontal overturning, geometric shielding, object shielding and the like are introduced, so that the robustness of a 2D
joint point detection network under complex
visual angle and shielding conditions is improved. And then an initial three-dimensional
human body posture is preliminarily estimated by using a
voxel space
back projection method through the detected multi-view 2D
heat map. For the
occlusion problem, a
visibility evaluation model fusing autologous
occlusion and
visual angle occlusion is constructed, and robust and stable
human body three-dimensional attitude
estimation can still be realized under the severe occlusion condition by introducing multiple constraints such as visual consistency,
time sequence continuity, attitude priori and skeleton consistency to optimize and predict a 3D attitude in a multi-stage manner. According to the method, high-precision and shielding-robust 3D
joint point detection can be realized only by inputting a multi-view-angle
RGB image during operation, and the method is suitable for a real scene with a complex shielding condition.