Any artificial agent acting in a real-world scenario should perform the analysis and interpretation of visual motion in a fast and reliable way. This task is effectively solved by the primate visual system, specifically in the dorsal cortical pathway, i.e. the ``action stream’’.
The dorsal pathway is organized in a hierarchical structure of layers that process the visual signal to extract simple image features that become more informative and complex in higher layers.
In this work, to fully exploit such an effective hierarchical approach adopted by the mammals’ visual system, we propose a bio-inspired vision system that mimics the first stages of the dorsal cortical pathway, i.e. the cortical motion pathway (namely V1-MT-MST).

In particular, we have considered the following processing stages:

• The front-end stage of the proposed bio-inspired vision system performs a space-variant image acquisition.
• The second stage is the computation of the optic flow through a distributed neural architecture that mimics the mechanisms underlying motion analysis in the areas V1 and MT.
• The final stage of the proposed vision system performs motion interpretation through a first order analysis of the optic flow that leads to orientation of surfaces and time-to contact (TTC) estimation