Human standing pose detection proposing mean eigenspace

Development of a mean eigenspace (MES) from some of selected human posture sets is proposed for detecting human standing postures. An average of several posture sets from some of selected subjects is used (instead of using just one set) fro creating MES and different unknown postures are recognized from it. In contrast to the conventional method, the paper proposes to employ image filtering to the input images for better performance of the eigenspace technique instead of using just original images for this particular study. For the selection of posture sets for the MES and for the recognition test, a leave out method is employed. The proposed approach of producing a MES is described and the robustness of the method is effectively proved in the experiment.