Human motion analysis and modeling

Abstract

Georgia Tech has investigated methods for the detection and tracking of personnel in a variety of acquisition environments. This research effort focused on a detailed phenomenological analysis of human physiology and signatures with the subsequent identification and characterization of potential observables. As a fundamental part of this research effort, Georgia Tech collected motion capture data on an individual for a variety of walking speeds, carrying loads, and load distributions. These data formed the basis for deriving fundamental properties of the individual's motion and supported the development of a physiologically-based human motion model. Subsequently this model aided the derivation and analysis of motion-based observables, particularly changes in the motion of various body components resulting from load variations. This paper will describe the data acquisition process, development of the human motion model, and use of the model in the observable analysis. Video sequences illustrating the motion data and modeling results will also be presented.