Research

Capabilities and consequences of recursive, hierarchical information processing in visual systems

A study on human and robot perception and the architecture of perceptual information processing

Research Unit: 1

Project Number: 2

Example Behavior:
Individual Intelligence

Disciplines:
Psychology
Robotics

 

Principal Investigators:
Martin Rolfs
Oliver Brock

Doctoral Researchers:
Aravind Battaje

Postdoctoral Researchers:
Nina Hanning
Angelica Godinez

 

Expected Project Duration
2019 - 2024


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Capabilities and consequences of recursive, hierarchical information processing in visual systems

A study on human and robot perception and the architecture of perceptual information processing

@SCIoI

This research project investigates human and robot perception and aims to develop a constructive understanding of perceptual information processing. We will create models using an information processing pattern that originated in robotics to understand perceptual mechanisms in human vision. The information processing pattern possesses similar high-level characteristics to human visual information processing, and thus has capabilities to generate similar behavior. We will apply this in an analytic-synthetic loop, simultaneously modeling while collecting psychophysical data, and adjusting the model with new observations. Based on the resulting insights we will produce an algorithmic model of human perception, capable of replicating visual 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.


Mengers, V., Battaje, A., Baum, M., & Brock, O. (2023). Combining Motion and Appearance for Robust Probabilistic Object Segmentation in Real Time. ICRA 2023. https://doi.org/10.1109/ICRA48891.2023.10160908
Godinez, A., Battaje, A., Brock, O., & Rolfs, M. (2023). Probing Perceptual Mechanism of Shape-Contingent Color after-Images via Interconnected Recursive Filters. Journal of Vision 23 / VSS 2023. https://doi.org/10.1167/jov.23.9.4885
Baum, M., Froessl, A., Battaje, A., & Brock, O. (2023). Estimating the Motion of Drawers From Sound. ICRA 2023. https://doi.org/10.1109/ICRA48891.2023.10161399
Battaje, A., Brock, O., & Rolfs, M. (2023). An Interactive Motion Perception Tool for Kindergarteners (and Vision Scientists). IPerception. https://doi.org/10.1177/20416695231159182
Battaje, A., Godinez, A., Hanning, N., Rolfs, M., & Brock, O. (2024). An Information Processing Pattern from Robotics Predicts Unknown Properties of the Human Visual System. bioRxiv. https://doi.org/10.1101/2024.06.20.599814
Battaje, A., & Brock, O. (2021). Interconnected Recursive Filters in Artificial and Biological Vision. DGR Days 2021, 32–32. https://www.static.tu.berlin/fileadmin/www/10002220/Publications/battaje21DGR.pdf
Battaje, A., & Brock, O. (2022). One Object at a Time: Accurate and Robust Structure From Motion for Robots. IROS 2022. https://doi.org/10.1109/IROS47612.2022.9981953

Research

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