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Capabilities and consequences of recursive, hierarchical information processing in visual systems
- © SCIoI
We investigate human and robot perception. The goal is to develop a constructive understanding of perceptual information processing, capitalizing on the analytic-synthetic loop. Our implementation of this concept is based on the concept of "optical cortex and robotic interactive perception algorithms". This resemblance is so striking because it spans various levels of abstraction and matches. Indeed, this computational architecture enables predictions that match observations in humans.
The project aims to leverage the fact that biological and robotic perception are inextricably linked to action. We will systematically identify computational features of the human visual system and transferring them to the algorithmic side. At the same time, we want to replicate hypotheses about human vision in the robotic system and investigate if their behavior is validate and explain human perceptual functions.
Revealing information processing mechanisms for perception also promises to provide insights about what we called “principles” of intelligence. We will tackle the following questions to gain insights:
- Is centralized or distributed approaches superior to the other? Or do they derive from differences in the substrate?
- To what degree should information processing be influenced by the perceptual objective?
- Does energetic economy relate to perceptual efficiency?
The project is funded by the SCIoI, Excellence Cluster, DFG.
Contact persons: Martin Rolfs, Oliver Brock