Computer Vision – From Surfaces to 3D Objects

Introduction Traditionally, the perception of three-dimensional (3D) scenes and objects was assumed to be the result of the reconstruction of 3D surfaces from available depth cues, such as binocular disparity, motion parallax, texture, and shading (Marr, 1982). In this approach, the role of figure-ground organization was kept to a minimum. Figure-ground organization refers to finding […]

The Operatorial Structure of the Cortex We will next reinterpret the neurogeometric structure introduced in the first part of the paper from a probabilistic point of view, replacing vector field generators of the Lie algebra by the corresponding operators. This operation is called in physics second quantization. FIGURE 7.5 A Kanitza triangle with curved boundaries […]

Introduction At the early processing stages in visual cortex, information is laid out in the form of maps of the retinal image. However, contrary to intuition, uniform surfaces are not mapped by uniform distributions of neural activity. We can perceive the three-dimensional (3D) shape of a uniform surface, but stereoscopic neurons are activated only by […]

Object-Related Coding The following simple model (Craft et al., 2007) explains our findings on border ownership coding and might also help us to understand how surfaces are represented by neurons (Figure 8.9). It proposes that border ownership selectivity is produced by specific neural grouping circuits (“G cells”) that integrate contour signals of V2 neurons (“B […]