Perceptual psychology and computer graphics ask many questions that are formally similar. These questions relate to how one can -- with rather limited resources -- extract, represent, and manipulate targeted portions of the vast amount of information present in the physical world. Over the last 150 years, perceptual psychologists have developed and refined a wide variety of experimental methods, and have gathered a wealth of detailed information about the algorithms that underlie human perceptual processes. Since many of the tasks and challenges explored in computer graphics are similar to those faced in human perception, and since humans are often the end-user of computer generated imagery, computer scientists are increasingly adapting knowledge about human perception to develop perceptually-inspired computer graphics algorithms. Moreover, computer graphics researchers are increasingly being asked to prove that newly developed techniques meet specific claims, such as "Are the images generated by the new method really indistinguishable from a photograph?"; "If not, why not?"; "Do the new visualizations really improve the performance of experts on specific tasks?" A firm understanding of perceptual research methodology will now only make it easier to comprehend and utilize existing knowledge about human perceptual capabilities, but will also enable you to ask and answer similar questions for your algorithms. In this talk, I will provide a brief overview of perceptual methodology and some of the fundamental assumptions that lie behind it.