A boundary-pair representation for perception modeling

It is widely accepted that responses from on- and off-center cells give rise to edges and are equivalent to edge detectors. In this paper, we point out that on- and off-center cell responses provide more information than edges. We show that an edge-based representation makes the ownership of boundaries ambiguous and requires a combinatorial search to model perceptual grouping. By analyzing the differences between edges and responses from on- and off-center cells, we propose a boundary-pair representation, which makes the ownership of boundaries explicit and eliminates the need of a combinatorial search computationally. Each boundary in the boundary-pair representation is associated with regional attributes. We show that this representation is equivalent to a surface representation through a local diffusion. This provides a unified representation for perception modeling. Based on this representation, a figure-ground segregation network is constructed to demonstrate the capabilities of the model in explaining many perceptual phenomena