Automatic Feature Localization in Thermal Images for Facial Expression Recognition
Abstract
We propose an unsupervised Local and Global feature extraction paradigm to approach the problem of facial expression recognition in thermal images. Starting from local, low-level features computed at interest point locations, our approach combines the localization of facial features with the holistic approach. The detailed steps are as follows: First, face localization using bi-modal thresholding is accomplished in order to localize facial features by way of a novel interest point detection and clustering approach. Second, we compute representative Eigenfeatures for feature extraction. Third, facial expression classification is made with a Support Vector Machine Committiee. Finally, the experiments over the IRIS data-set show that automation was achieved with good feature localization and classification performance.
Cite
Text
Trujillo et al. "Automatic Feature Localization in Thermal Images for Facial Expression Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005. doi:10.1109/CVPR.2005.415Markdown
[Trujillo et al. "Automatic Feature Localization in Thermal Images for Facial Expression Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2005.](https://mlanthology.org/cvpr/2005/trujillo2005cvpr-automatic/) doi:10.1109/CVPR.2005.415BibTeX
@inproceedings{trujillo2005cvpr-automatic,
title = {{Automatic Feature Localization in Thermal Images for Facial Expression Recognition}},
author = {Trujillo, Leonardo and Olague, Gustavo and Hammoud, Riad I. and Hernández, Benjamín},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2005},
pages = {14},
doi = {10.1109/CVPR.2005.415},
url = {https://mlanthology.org/cvpr/2005/trujillo2005cvpr-automatic/}
}