The goal of this project is to understand how the human visual system uses texture and contour information to perceive the spatial layout of surfaces in the environment. One result of computational analyses of texture and contour information, as well as some demonstrations, is that multiple, different constraints may be used to aid in the interpretation of surface geometry,reflecting the essential categorical structure of the environment which gives rise to the constraints. The proposed research will focus on uncovering the structure of the constraints which the visual system uses and the strategies by which it determines which constraints to apply. The proposed strategy will be to investigate how texture and contour information interacts with other normally available cues like stereo, accommodation and blur to determine percepts of surface geometry. Patterns of interaction between the cues, such as how texture and contour information bias interpretations of surface geometry from stereo, will be used to investigate the constraint structure underlying the interpretation of texture and contour information-what constraints the visual system can use and how it determines which constraints to impose for any given scene; for example, whether and how the visual system uses stereo information cooperatively with texture and contour cues to determine what constraints are appropriate to use for cue interpretation. The research will involve a significant methodological advance over previous work. We will study the perceptual interpretation of texture and surface contour information in semi-naturalistic stimuli, which we will generate by projecting texture or contour patterns onto real surfaces viewed binocularly. The physical set-up for stimulus projection will enable us to manipulate the 3D orientations of viewed surfaces independently of the patterns projected on them. By using surfaces oriented in depth for stimuli, we reduce the conflicts inherent in simulated 3D displays presented on a CRT; including both gross conflicts between cues and conflicts between different perceptual modes of stimulus interpretation; that is, as 2D patterns projected on a fronto-parallel display or as pictorial representations of 3D scenes. The results will provide a deeper understanding of the microstructure of texture and contour cues for 3D surface geometry.
| Saunders, Jeffrey A; Knill, David C (2004) Visual feedback control of hand movements. J Neurosci 24:3223-34 |
| Knill, David C (2003) Mixture models and the probabilistic structure of depth cues. Vision Res 43:831-54 |
| Saunders, Jeffrey A; Knill, David C (2003) Humans use continuous visual feedback from the hand to control fast reaching movements. Exp Brain Res 152:341-52 |
| Knill, D C (2001) Contour into texture: information content of surface contours and texture flow. J Opt Soc Am A Opt Image Sci Vis 18:12-35 |
| Knill, D C (1998) Discrimination of planar surface slant from texture: human and ideal observers compared. Vision Res 38:1683-711 |
| Jeka, J J; Schoner, G; Dijkstra, T et al. (1997) Coupling of fingertip somatosensory information to head and body sway. Exp Brain Res 113:475-83 |
| Knill, D C; Mamassian, P; Kersten, D (1997) Geometry of shadows. J Opt Soc Am A Opt Image Sci Vis 14:3216-32 |
| Kersten, D; Mamassian, P; Knill, D C (1997) Moving cast shadows induce apparent motion in depth. Perception 26:171-92 |
