Labeling of human body parts

A novel method for human body parts labeling, given a set of body parts that are represented by bars in the image is developed. First, we assume that in addition to the head and torso, the human body has 8 major body parts namely, the upper and lower arms (left and right) and the upper and lower legs (left and right) and all these parts can be approximated by cylinders that appear as rectangular bars in the image. One of the original contributions of this paper is the novel use of the spatial distributions of the location and orientation of the bars employed to find a correct role assignment for each bar by maximizing a joint probability function. Thus, we formulate the problem of labeling human body parts as an optimal hypothesis selection problem where each hypothesis corresponds to a particular role assignment. Next, we develop an algorithm which identifies the optimal hypothesis. We test our method with 80 images that depict human poses and obtain correct labeling in 98.7% of the trials. We also test our method in cases of bar detection errors, occlusion and noisy images and obtain quite good results.