Falls are a significant cause of mortality and serious injury in older adults and particularly in people with neurological disorders. The ability to maintain balance and postural control is commonly evaluated using center of pressure (COP) data collected with a force platform. Recent methods such as the Stabilogram Diffusion Analysis (SDA) have examined the stochastic characteristics of the COP but require numerous, long duration trials for reliable measures. To further our understanding of the underlying dynamical processes in postural control, we propose a new conceptual framework for studying human postural control using the COP velocity autocorrelation function (COP-VAF), and compare its results to SDA. Five healthy young participants were studied under quiet standing conditions with either eyes open or closed. COP trajectories were analyzed using both traditional posturographic measures, SDA, and the COP-VAF. It is shown that the COP-VAF leads to repeatable, physiologically meaningful measures that can distinguish postural control differences with and without vision in healthy individuals. More specifically, visual feedback was found to significantly decrease the peak COP velocity autocorrelation value and magnitude of the first minimum, while increasing the diffusion coefficient. This result is interpreted as an indication that visual input serves to rapidly eliminate any oscillatory motion in quiet stance and utilizes a smaller potential field to maintain balance. In contrast to SDA, COP-VAF measures provide a more concise and reliable measure of postural control (intraclass coefficient correlation (ICC) = 0.23-0.87 vs. 0.05-0.91 in COP-VAF vs. SDA measures, respectively). This work suggests that we can further extend our understanding of the underlying mechanisms behind postural control in quiet stance using the COP-VAF and may apply this analysis in quantifying future neurorehabilitative interventions aimed at improving balance.