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Updated: Oct 22, 2025
07:05
Applying Hyperspectral Reflectance Imaging to Investigate the Palettes and the Techniques of Painters
Published on: June 18, 2021
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Materials In Paintings (MIP): An interdisciplinary dataset for perception, art history, and computer vision.
Mitchell J P Van Zuijlen1, Hubert Lin2, Kavita Bala2
1Perceptual Intelligence Lab, Delft University of Technology, Delft, The Netherlands.
Plos One
|August 26, 2021
Summary
This study introduces a dataset of paintings with material labels, enabling research into how artists depict materials. This resource aids studies in human perception, art history, and computer vision.
Area of Science:
- Computer Vision
- Art History
- Human Perception
Background:
- Understanding material depiction in art is crucial for cross-disciplinary research.
- Existing datasets lack comprehensive material annotations for paintings.
Purpose of the Study:
- To create and release a large-scale dataset of annotated paintings focusing on material depictions.
- To explore the cross-disciplinary applications of this dataset in perception, art history, and computer vision.
Main Methods:
- Annotated 19,000 paintings with over 200,000 bounding boxes for material labels (coarse and fine-grained).
- Developed methods for automatic polygon segment extraction from bounding boxes.
- Made the dataset publicly available for download and browsing.
Main Results:
- Demonstrated how painters use stylized approaches for convincing material depiction.
- Analyzed spatial and probabilistic distributions of materials in paintings, revealing strong patterns.
- Showcased the dataset's utility in building more robust computer vision classifiers with perceptually relevant features.
- Uncovered hidden perceptual cues by training classifiers on paintings and visualizing features.
Conclusions:
- The dataset of painterly material depictions offers rich insights into material representation and perception.
- The dataset is expected to foster multidisciplinary research across art, perception, and computer science.
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