Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 68-77).Humans are able to simultaneously perceive the world as discrete, distinct "objects", as well as regions of statistical regularity, or "textures". This is evident in the way we describe our perceptual world. A street is made up of concrete and asphalt "stuff", while the people and dogs walking on it are the "things" that make use of it. Both of these types of representation, however, are derived from the same sensory input, and thus there must exist transformations that map one to the other. A complete model of perception must account for these transformations. I study the representations that lie at the interface of object and texture perception in vision, focusing on utilizing the intrinsically impaired perception in the periphery to disambiguate the predictions of different models. I find that many seemingly separate perceptual phenomena in crowding can be better understood as different aspects of a single underlying model. I extend this to the study of material perception, and find that considering images of materials as visual textures can explain human's ability to recognize materials in the periphery. Furthermore, I examine how the limitations of peripheral vision affects the perception of visual designs, namely webpages.by Shaiyan Keshvari.Ph. D.