Choreographing the Digital Canvas: A Machine Learning Approach to Artistic Performance

arXiv:2404.00054v1 Announce Type: cross
Abstract: This paper introduces the concept of a design tool for artistic performances based on attribute descriptions. To do so, we used a specific performance of falling actions. The platform integrates a novel machine-learning (ML) model with an interactive interface to generate and visualize artistic movements. Our approach's core is a cyclic Attribute-Conditioned Variational Autoencoder (AC-VAE) model developed to address the challenge of capturing and generating realistic 3D human body motions from motion capture (MoCap) data. …

abstract arxiv canvas concept cs.gr cs.hc cs.lg design digital generate interactive machine machine learning novel paper performance performances platform tool type