Seeing Stuff: Perceiving Materials and their Properties
STUFF aims to uncover how we perceive and interact with various materials by integrating methods from psychology, neuroscience, and computer science to enhance our understanding of material properties.
Projectdetails
Introduction
Different materials, such as silk, soil, steel, and soap, exhibit an astonishing variety of physical properties, appearances, and behaviors. The material properties of objects and substances are central to practically every task we perform, from selecting and preparing food to detecting slippery ground and using tools effectively. Without touching a surface, we usually enjoy a vivid impression of what it would feel like through the sense of sight. Yet, how we do so remains mysterious.
Research Focus
Decades of research have focused on the visual recognition of objects, faces, and scenes. By comparison, how we see, think about, and interact with ‘stuff’ has been relatively neglected. STUFF addresses this major gap in our understanding.
Challenges in Material Perception
Material perception poses unique and fascinating challenges. The image of a surface is a complex and ambiguous combination of lighting, shape, and material properties.
Key Questions
- How does the visual system disentangle these intermingled physical factors?
- Deformable materials like liquids and textiles move and change shape in complex yet lawful ways. How do we infer intrinsic properties like viscosity, compliance, and elasticity from such ever-changing stimuli?
- How do we reason about and predict their future behaviors as they interact with their surroundings?
- How do we adapt our own interactions with objects to take into consideration their hardness, density, friction, and other physical characteristics, allowing us to pluck a raspberry without crushing it or pick up wet soap without it slipping through our fingers?
Interdisciplinary Approach
STUFF takes a radically interdisciplinary approach to these questions in five tightly interconnected work packages. This initiative brings together state-of-the-art methods from:
- Experimental psychology and behavioral neuroscience
- Computer graphics and computational image analysis
- Machine learning
- Art
We draw on real and simulated materials to uncover how we perceive, reason about, predict, and interact with materials and their properties.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.499.711 |
Totale projectbegroting | € 2.499.711 |
Tijdlijn
Startdatum | 1-10-2023 |
Einddatum | 30-9-2028 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- JUSTUS-LIEBIG-UNIVERSITAET GIESSENpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
Project | Regeling | Bedrag | Jaar | Actie |
---|---|---|---|---|
Life-Inspired Soft MatterThis project aims to develop life-inspired materials with adaptive properties through dynamic control mechanisms, enabling applications in human-device interfaces and soft robotics. | ERC Advanced... | € 2.500.000 | 2024 | Details |
Inter materials and structures mechanoperception for self learningIMMENSE aims to develop self-learning, adaptive materials and structures that can sense, signal, and react to environmental stimuli, paving the way for innovative applications in various fields. | ERC Advanced... | € 2.500.000 | 2024 | Details |
Multimodal Sensory-Motorized Material SystemsMULTIMODAL aims to create advanced sensory-motorized materials that autonomously respond to environmental stimuli, enabling innovative soft robots with adaptive locomotion and interactive capabilities. | ERC Consolid... | € 1.998.760 | 2023 | Details |
SynthAct3D: Pioneering 3D Real-Space Studies of Synthetic Active MatterSynthAct3D aims to advance synthetic self-propelled particles from 2D to 3D to explore emergent behaviors and develop reconfigurable active materials for innovative applications. | ERC Consolid... | € 2.000.000 | 2025 | Details |
Gestalts Relate Aesthetic Preferences to Perceptual AnalysisThis project aims to link aesthetic preferences to perceptual analysis by investigating how sensory organization influences taste, using machine learning and empirical studies in art and everyday images. | ERC Advanced... | € 2.497.701 | 2022 | Details |
Life-Inspired Soft Matter
This project aims to develop life-inspired materials with adaptive properties through dynamic control mechanisms, enabling applications in human-device interfaces and soft robotics.
Inter materials and structures mechanoperception for self learning
IMMENSE aims to develop self-learning, adaptive materials and structures that can sense, signal, and react to environmental stimuli, paving the way for innovative applications in various fields.
Multimodal Sensory-Motorized Material Systems
MULTIMODAL aims to create advanced sensory-motorized materials that autonomously respond to environmental stimuli, enabling innovative soft robots with adaptive locomotion and interactive capabilities.
SynthAct3D: Pioneering 3D Real-Space Studies of Synthetic Active Matter
SynthAct3D aims to advance synthetic self-propelled particles from 2D to 3D to explore emergent behaviors and develop reconfigurable active materials for innovative applications.
Gestalts Relate Aesthetic Preferences to Perceptual Analysis
This project aims to link aesthetic preferences to perceptual analysis by investigating how sensory organization influences taste, using machine learning and empirical studies in art and everyday images.