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. Both aspects are needed to support the
development of personnel detection and tracking algorithms. 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 the derivation of motionbased
observables, and changes in these fundamental properties arising from load variations. Analyses were conducted
to characterize the motion properties of various body components such as leg swing, arm swing, head motion, and full
body motion. This paper will describe the data acquisition process, extraction of motion characteristics, and analysis of
these data. Video sequences illustrating the motion data and analysis results will also be presented.