Extraction of surface-related features in a recurrent model of V1-V2 interactions.

ABSTRACT:

Background

Humans can effortlessly segment surfaces and objects from two-dimensional (2D) images that are projections of the 3D world. The projection from 3D to 2D leads partially to occlusions of surfaces depending on their position in depth and on viewpoint. One way for the human visual system to infer monocular depth cues could be to extract and interpret occlusions. It has been suggested that the perception of contour junctions, in particular T-junctions, may be used as cue for occlusion of opaque surfaces. Furthermore, X-junctions could be used to signal occlusion of transparent surfaces.

Methodology/principal findings

In this contribution, we propose a neural model that suggests how surface-related cues for occlusion can be extracted from a 2D luminance image. The appr

SUBMITTER: Weidenbacher U 

PROVIDER: S-EPMC2691604 | biostudies-literature | 2009 Jun

REPOSITORIES: biostudies-literature