Exploring Fungal Morphology Simulation and Dynamic Light Containment from a Graphics Generation Perspective
<|reference_start|>Exploring Fungal Morphology Simulation and Dynamic Light Containment from a Graphics Generation Perspective: Fungal simulation and control are considered crucial techniques in Bio-Art creation. However, coding algorithms for reliable fungal simulations have posed significant challenges for artists. This study equates fungal morphology simulation to a two-dimensional graphic time-series generation problem. We propose a zero-coding, neural network-driven cellular automaton. Fungal spread patterns are learned through an image segmentation model and a time-series prediction model, which then supervise the training of neural network cells, enabling them to replicate real-world spreading behaviors. We further implemented dynamic containment of fungal boundaries with lasers. Synchronized with the automaton, the fungus successfully spreads into pre-designed complex shapes in reality.<|reference_end|>
@article{wang2024exploring,
    title={Exploring Fungal Morphology Simulation and Dynamic Light Containment
  from a Graphics Generation Perspective},
    author={Kexin Wang, Ivy He, Jinke Li, Ali Asadipour, Yitong Sun},
    journal={arXiv preprint arXiv:2409.05171},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.05171},
    primaryClass={cs.GR cs.CV cs.HC cs.LG}
}