A model-free approach for posture classification

This paper describes a peculiar methodology for identifying and classifying the human body structures depicted in digital images. The methodology is articulated in a number of successive steps: an initial process of motion detection recognises human targets into the examined scene; subsequently, a synthetic representation of the previously detected human figures is obtained in form of skeleton, by means of a thinning operator. Finally, the pose estimation step is performed on the basis of a geometrical analysis conducted over a set of features related to the extracted skeletons. Experimental evidence of the appropriateness of the overall methodology is also presented.