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This article presents a novel background technique that enables one to distinguish correlated motion of colloidal particles from random thermal effects and projection effects in video microscopy recordings that have been converted into digital lists of apparent particle trajectories. The idea is that one can construct reference data sets lacking any correlated motion from actual observations by randomly translating single particle trajectories. One, therefore, detects genuine correlations with a statistical measure by comparing the results for the original and background data sets. The success of this technique is demonstrated here by numerical simulations. © 1996 American Institute of Physics.