Brazilian Sign Language Recognition Using Kinect
Abstract
The simultaneous-sequential nature of sign language production, which employs hand gestures and body motions combined with facial expressions, still challenges sign language recognition algorithms. This paper presents a method to recognize Brazilian Sign Language (Libras) using Kinect. Skeleton information is used to segment sign gestures from a continuous stream, while depth information is used to provide distinctive features. The method was assessed in a new data-set of 107 medical signs selected from common dialogues in health-care centers. The dynamic time warping–nearest neighbor (DTW-kNN) classifier using the leave-one-out cross-validation strategy reported outstanding results.
Cite
Text
Vidalón and De Martino. "Brazilian Sign Language Recognition Using Kinect." European Conference on Computer Vision, 2016. doi:10.1007/978-3-319-48881-3_27Markdown
[Vidalón and De Martino. "Brazilian Sign Language Recognition Using Kinect." European Conference on Computer Vision, 2016.](https://mlanthology.org/eccv/2016/vidalon2016eccv-brazilian/) doi:10.1007/978-3-319-48881-3_27BibTeX
@inproceedings{vidalon2016eccv-brazilian,
title = {{Brazilian Sign Language Recognition Using Kinect}},
author = {Vidalón, José Elías Yauri and De Martino, José Mario},
booktitle = {European Conference on Computer Vision},
year = {2016},
pages = {391-402},
doi = {10.1007/978-3-319-48881-3_27},
url = {https://mlanthology.org/eccv/2016/vidalon2016eccv-brazilian/}
}