Abstract
This paper presents a study on the role of dynamic motions in the creation and perception processes of action-art paintings. Although there is a lot of interest and some qualitative knowledge around, there are no quantitative models in the scientific computing sense about this process yet. To create such models and implement them on a robotic platform is the objective of our work. Therefore, we performed motion capture experiments with an artist and reconstructed the recorded motions by fitting the data to a rigid-body model of the artist’s arm. A second model of a 6-DOF robotic platform is used to generate new motions by means of optimization and optimal control algorithms. Additionally, we present an image analysis framework that computes certain image characteristics related to aesthetic perception and a web tool that we developed to perform online sorting and cluster studies with participants. We present first results concerning motion reconstruction and perception studies and give an outlook to what will be the next steps towards an autonomous painting robotic platform.
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Acknowledgements
The authors want to thank the Simulation and Optimization research group of IWR at the University of Heidelberg for the permission to work with the software package MUSCOD-II. We greatfully acknowledge financial and scientific support that was given by the Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences, funded by DFG (Deutsche Forschungsgemeinschaft). We also greatfully acknowledge financial travel support granted by DAAD (Deutscher Akademischer Austauschdienst). Finally, we want to thank Nicole Suska for the possibility to perform motion capture experiments with her.
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Schubert, A., Mombaur, K., Funke, J. (2014). Mathematical Models of Perception and Generation of Art Works by Dynamic Motions. In: Bock, H., Hoang, X., Rannacher, R., Schlöder, J. (eds) Modeling, Simulation and Optimization of Complex Processes - HPSC 2012. Springer, Cham. https://doi.org/10.1007/978-3-319-09063-4_17
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DOI: https://doi.org/10.1007/978-3-319-09063-4_17
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