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This paper investigates a human body posture estimation method based on the back projection of human silhouette images extracted from multi-camera images. The multi-camera system is based on a server-client system with local network of 1000 Base-T to achieve a voxel 3D reconstruction of human body posture in real-time. In order to extract significant points of the human body such as head, neck, shoulders, elbow joints, hands, waist, knee joints, and toes in 3D, an articulated cylindrical human model is applied to the voxel reconstruction of human body. To evaluate the proposed human body posture estimation method, 3D reconstruction experiments of human body posture and extraction experiments of human bodypsilas significant points are carried out. The system runs in real time (9 frames/sec with 50 times 50 times 50 voxel resolution) and the experimental results confirm both the feasibility and effectiveness of the proposed system in 3D human body posture estimation.