An Asymmetrical Diffusion Framework for Junction Analysis

The diffusion framework exhibits many promising properties for the purposes of junction analysis. In its most common form, images are diffused either isotropically or with respect to gradient information in an anisotropical fashion. This information is then collected into an orientational distribution function (ODF) and the resulting features are modeled as ’X’, ’Y’ or ’T’shaped junctions. Specific to the spatio-temporal domain, and in particular, a 2D spatio-temporal slice, points of kinetic-based occlusion are identified by T-junctions while points of kinetic-transparency form X-junctions. The challenge is that most forms of diffusion are symmetric in their representation and are unable to properly distinguish between these two junction types. This work proposes to diffuse information asymmetrically and investigates the differences between weighting the iterative diffusion isotropically versus as an ODF-shaped region of influence function.