Neural-network-based real-time human body posture estimation

This paper proposes a real-time human body posture estimation method using ANNs. The network is composed of three ANNs and a decision logic unit. The ANNs´ input is the result of a function analysis on a human silhouette´s contour extracted from camera images and the ANNs´ output indicates the feature points´ positions on the contour. The decision logic unit synthesizes each of the ANNs´ output vectors and then the 2D coordinates of the human body´s feature points are calculated. The proposed method is implemented on a personal computer and runs in real-time (17-20 frames/sec). Experimental results confirm both the feasibility and the effectiveness of the proposed method for estimating human body postures