Modeling Dynamic Scenes with Active Appearance
Abstract
In this work, we propose a model for video scenes that contains temporal variability in shape and appearance. We propose a conditionally linear model akin to a dynamic extension of active appearance models. We formulate the problem variationally, and propose a framework where a model complexity cost dictates the "modeling responsibility" of each of the factors: appearance, shape and motion. We render the learning problem well-posed by reverting to a physical and a dynamic prior, and use the finite element method to compute a numerical solution. We illustrate our model to learn and simulate the shape, appearance, and motion of scenes that exhibit some form of temporal regularity, intended in a statistical sense.
Cite
Text
Doretto. "Modeling Dynamic Scenes with Active Appearance." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.226Markdown
[Doretto. "Modeling Dynamic Scenes with Active Appearance." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/doretto2005cvpr-modeling/) doi:10.1109/CVPR.2005.226BibTeX
@inproceedings{doretto2005cvpr-modeling,
title = {{Modeling Dynamic Scenes with Active Appearance}},
author = {Doretto, Gianfranco},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2005},
pages = {66-73},
doi = {10.1109/CVPR.2005.226},
url = {https://mlanthology.org/cvpr/2005/doretto2005cvpr-modeling/}
}