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1. Phenotypic Trait of Painting Cracks

   https://doi.org/10.1080/00393630.2024.2420574  

   Abu-Haifa, Mohammad; Lee, Seung Jae; Zhu, Cheng (November 2024, Studies in Conservation)

   A painting, like human skin, develops cracks on the surface as it dries and ages. The painting cracks, also known as craquelure, are often considered analogous to human fingerprints; these have been regarded as a unique signature reflective of the painting’s characteristics and are important in art authentication. Intriguingly, studies in other fields, such as geology, have observed the presence of distinctive characteristics in soil desiccation cracks. These cracks exhibit self-similarity, forming patterns that suggest broader geological processes at work. In light of this connection, the primary objective of this study is to investigate whether the painting cracks also exhibit a self-similar nature. By delving into this, we seek to shed light on the underlying properties of the painting cracks. This study also aims to investigate whether the characteristic self-similar trait of the cracks can serve as an identifier in relation to the provenances of the paintings. To this end, this study adopts the methodology originally designed to characterize the phenotypic traits of 3D particle geometries in granular materials research. This study develops a 2D equivalent concept, focusing on the phenotypic traits of the individual islands enclosed by cracks within paintings. The results successfully demonstrate that the phenotypic trait of painting cracks exhibits a self-similar nature, which can reveal characteristics associated with the provenances of paintings. The findings will offer valuable insights into the scientific examination of artworks based on painting cracks. 

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2. Robotic painting: mimicking human applicators

   https://doi.org/10.1007/s11998-022-00750-7  

   Bansal, Karan; Du, Yayun; Palan, Eric; Quadir, Mohiuddin; Khalid Jawed, Mohammad (March 2023, Journal of Coatings Technology and Research)

   Abstract Robotically assisted painting is widely used for spray and dip applications. However, use of robots for coating substrates using a roller applicator has not been systematically investigated. We showed for the first time, a generic robot arm-supported approach to painting engineering substrates using a roller with a constant force at an accurate joint step, while retaining compliance and thus safety. We optimized the robot design such that it is able to coat the substrate using a roller with a performance equivalent to that of a human applicator. To achieve this, we optimized the force, frequency of adjustment, and position control parameters of robotic design. A framework for autonomous coating is available athttps://github.com/duyayun/Vision-and-force-control-automonous-painting-with-rollers; users are only required to provide the boundary coordinates of surfaces to be coated. We found that robotically- and human-painted panels showed similar trends in dry film thickness, coating hardness, flexibility, impact resistance, and microscopic properties. Color profile analysis of the coated panels showed non-significant difference in color scheme and is acceptable for architectural paints. Overall, this work shows the potential of robot-assisted coating strategy using roller applicator. This could be a viable option for hazardous area coating, high-altitude architectural paints, germs sanitization, and accelerated household applications. 

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3. Vectorized Painting with Temporal Diffusion Curves

   https://doi.org/10.1109/TVCG.2019.2929808  

   Li, Yingjia; Zhai, Xiao; Hou, Fei; Liu, Yawen; Hao, Aimin; Qin, Hong (January 2021, IEEE Transactions on Visualization and Computer Graphics)

   null (Ed.)
4. Deep multispectral painting reproduction via multi-layer, custom-ink printing

   https://doi.org/10.1145/3272127.3275057  

   Shi, Liang; Babaei, Vahid; Kim, Changil; Foshey, Michael; Hu, Yuanming; Sitthi-Amorn, Pitchaya; Rusinkiewicz, Szymon; Matusik, Wojciech (January 2019, ACM Transactions on Graphics)
5. A measure of visuospatial reasoning skills: Painting the big picture

   Michelson, J.; Sanyal, D.; Ainooson, J.; Kunda, M. (January 2020, Proceedings of the Eighth Annual Conference on Advances in Cognitive Systems (ACS))

   null (Ed.)

   Visuospatial reasoning refers to a diverse set of skills that involve thinking about space and time. An artificial agent with access to a sufficiently large set of visuospatial reasoning skills might be able to generalize its reasoning ability to an unprecedented expanse of tasks including portions of many popular intelligence tests. In this paper, we stress the importance of a developmental approach to the study of visuospatial reasoning, with an emphasis on fundamental skills. A comprehensive benchmark, with properties we outline in this paper including breadth, depth, explainability, and domain-specificity, would encourage and measure the genesis of such a skillset. Lacking an existing benchmark that satisfies these properties, we outline the design of a novel test in this paper. Such a benchmark would allow for expanding analysis of existing datasets’ and agents’ applicability to the problem of generalized visuospatial reasoning. 

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