Human motion analysis has seen drastic improvements recently, however, due to the lack of representative datasets, for clinical in-bed scenarios it is still lagging behind. To address this issue, we implemented BlanketGen, a pipeline that augments videos with synthetic blanket occlusions. With this pipeline, we generated an augmented version of the pose estimation dataset 3DPW called BlanketGen-3DPW. We then used this new dataset to fine-tune a Deep Learning model to improve its performance in these scenarios with promising results. Code and further information are available at https://gitlab.inesctec.pt/brain-lab/brain-lab-public/blanket-gen-releases.
@article{arxiv.2210.12035,
title = {BlanketGen - A synthetic blanket occlusion augmentation pipeline for MoCap datasets},
author = {João Carmona and Tamás Karácsony and João Paulo Silva Cunha},
journal= {arXiv preprint arXiv:2210.12035},
year = {2023}
}
Comments
4 pages, Code and further information to generate the dataset is available at: https://gitlab.inesctec.pt/brain-lab/brain-lab-public/blanket-gen-releases