Berio, D., Calinon, S., Plamondon, R. and Leymarie, F. F. (2025)
Differentiable rasterization of minimum-time sigma-lognormal trajectories
In Proc. 22nd Conference of the International Graphonomics Society (IGS).
Abstract
We present an adaptation of the sigma-lognormal model to generate and fit smooth trajectories in conjunction with a differentiable vector graphics (DiffVG) rendering pipeline and with parameter selection driven by a minimum-time smoothing criterion. This approach enables the incorporation of the ``Kinematic Theory of Rapid Human Movements'' into modern image-based deep learning systems. We demonstrate its utility through various applications, including fitting handwriting trajectories to an image and generating trajectories using guidance from a large multimodal model.
Bibtex reference
@inproceedings{Berio25IGS,
author={Berio, D. and Calinon, S. and Plamondon, R. and Leymarie, F. F.},
title={Differentiable rasterization of minimum-time sigma-lognormal trajectories},
booktitle={22nd Conference of the International Graphonomics Society ({IGS})},
year={2025}
}