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Item Sketching and Layering Graffiti Primitives(The Eurographics Association, 2019) Berio, Daniel; Asente, Paul; Echevarria, Jose; Leymarie, Frederic Fol; Kaplan, Craig S. and Forbes, Angus and DiVerdi, StephenWe present a variant of the skeletal strokes algorithm aimed at mimicking the appearance of hand made graffiti art. It includes a unique fold-culling process that stylizes folds rather than eliminating them. We demonstrate how the stroke structure can be exploited to generate non-global layering and self-overlap effects like the ones that are typically seen in graffiti art and other related art forms like traditional calligraphy. The method produces vector output with no artificial artwork splits, patches or masks to render the non-global layering; each path of the vector output is part of the desired outline. The method lets users interactively generate a wide variety of stylised outputs.Item ACM/EG Expressive Symposium 2025 Posters and Demos: Frontmatter(The Eurographics Association, 2025) Berio, Daniel; Bruckert, Alexandre; Berio, Daniel; Bruckert, AlexandreItem Robotic Painting using Semantic Image Abstraction(The Eurographics Association, 2025) Stroh, Michael; Paetzold, Patrick; Berio, Daniel; Leymarie, Frederic Fol; Kehlbeck, Rebecca; Deussen, Oliver; Berio, Daniel; Bruckert, AlexandreWe present a novel image segmentation and abstraction pipeline tailored to robot painting applications. We address the unique challenges of realizing digital abstractions as physical artistic renderings. Our approach generates adaptive, semantics-based abstractions that balance aesthetic appeal, structural coherence, and practical constraints inherent to robotic systems. By integrating panoptic segmentation with color-based over-segmentation, we partition images into meaningful regions corresponding to semantic objects while providing customizable abstraction levels we optimize for robotic realization. We employ saliency maps and color difference metrics to support automatic parameter selection to guide a merging process that detects and preserves critical object boundaries while simplifying less salient areas. Graph-based community detection further refines the abstraction by grouping regions based on local connectivity and semantic coherence. These abstractions enable robotic systems to create paintings on real canvases with a controlled level of detail and abstraction.Item LABOR: Production of a Large-scale Painting with a Robot(The Eurographics Association, 2025) Grayver, Liat; Berio, Daniel; Herrmann, Inge; Notz, Adrian; Berio, Daniel; Bruckert, AlexandreLabor is a live human/robot painting installation that combines generative graphics techniques, robotic automation and traditional painting methods. It explores the role of embodied intelligence in artistic production. The resulting composition is a large-scale painting consisting of multiple individually painted tiles. The painting is based on an electron microscope image of a placenta, which is algorithmically processed into a series of parametric brushstrokes using a differentiable vector graphics pipeline. These strokes are then collaboratively painted using a 7-axis robotic arm equipped with custom paintbrushes. The project engages with the dual meaning of ''labor'': industrial production and childbirth, highlighting the often-overlooked importance of bodily knowledge in the arts but particularly in medical and technological contexts. The installation explores the balance between human intuition and algorithmic automation, emphasizing the importance of material constraints and the role of human artists in the creation a large-scale generative painting.