EXC 2002/1: Capabilities and Consequences of Recursive, Hierarchical Information Processing in Visual Systems (SP 02)

This research project investigates human and robot perception and aims to develop a constructive understanding of perceptual information processing. This will be done by setting up a hierarchical functional architecture for synthetic perceptual systems to uncover potential consequences that can be tested psychophysically in these systems and compared to performance of humans. By examining the resulting analytic-synthetic loop, we will derive intelligent principles of processing in hierarchical perceptual systems, discover discrepancies from these principles in biological implementations (i.e. in humans) and, ideally, determine the sources of potential constraints revealed by the data collected in human participants. Based on the resulting insights we will produce an algorithmic model of human perception, capable of replicating observed phenomena and of making meaningful predictions about experimental outcomes. We will also produce robot perception algorithms that leverage insights about the human perceptual system to advance the state of the art in the synthetic disciplines.

Principal investigators
Rolfs, Martin Prof. Dr. (Details) (General Psychology - Active Perception and Cognition)

Participating external organisations

DFG Excellence Strategy: Cluster

Duration of project
Start date: 10/2019
End date: 09/2024

Related umbrella project

Research Areas
Computer Science, Educational Research, Neurosciences, Psychology, Systems Engineering

Research Areas
Kognitive Robotik, Neuronale Informationsverarbeitung

Last updated on 2022-16-12 at 05:30