dc.contributor.author | Farooq, Muhammad Ali | |
dc.contributor.author | Corcoran, Peter | |
dc.date.accessioned | 2021-05-24T11:52:35Z | |
dc.date.available | 2021-05-24T11:52:35Z | |
dc.date.issued | 2020-05-26 | |
dc.identifier.citation | Farooq, Muhammad Ali, & Corcoran, Peter. (2020). Generating thermal image data samples using 3D facial modelling techniques and deep learning methodologies. Paper presented at the 12th International Conference on Quality of Multimedia Experience (QoMEX), Athlone, Ireland, 26-28 May. https://doi.org/10.1109/qomex48832.2020.9123079 | en_IE |
dc.identifier.uri | http://hdl.handle.net/10379/16782 | |
dc.description.abstract | Methods for generating synthetic data have become of increasing importance to build large datasets required for Convolution Neural Networks (CNN) based deep learning techniques for a wide range of computer vision applications. In this work, we extend existing methodologies to show how 2D thermal facial data can be mapped to provide 3D facial models. For the proposed research work we have used tufts datasets for generating 3D varying face poses by using a single frontal face pose. The system works by refining the existing image quality by performing fusion based image preprocessing operations. The refined outputs have better contrast adjustments, decreased noise level and higher exposedness of the dark regions. It makes the facial landmarks and temperature patterns on the human face more discernible and visible when compared to original raw data. Different image quality metrics are used to compare the refined version of images with original images. In the next phase of the proposed study, the refined version of images is used to create 3D facial geometry structures by using Convolution Neural Networks (CNN). The generated outputs are then imported in blender software to finally extract the 3D thermal facial outputs of both males and females. The same technique is also used on our thermal face data acquired using prototype thermal camera (developed under Heliaus EU project) in an indoor lab environment which is then used for generating synthetic 3D face data along with varying yaw face angles and lastly facial depth map is generated. | en_IE |
dc.description.sponsorship | This research is supported and funded by the Heliaus
European Union Project. The project focused on enabling safe
autonomous driving systems. This project has received funding
from the ECSEL Joint Undertaking (JU) under grant agreement
No 826131. The JU receives support from the European
Union’s Horizon 2020 research and innovation program and
France, Germany, Ireland, Italy. The authors would like to
acknowledge Shubhajit Basak for providing his support to use
blender software, the Xperi Ireland team and Quentin Noir from
Lynred France for giving their feedback. Moreover, authors
would like to acknowledge tufts university the contributors of
the tufts dataset for providing the image resources to carry out
this research work. | en_IE |
dc.format | application/pdf | en_IE |
dc.language.iso | en | en_IE |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_IE |
dc.relation.ispartof | 2020 Twelfth International Conference on Quality of Multimedia Experience (QoMEX) | en |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Ireland | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ | |
dc.subject | thermal | en_IE |
dc.subject | CNN | en_IE |
dc.subject | synthetic | en_IE |
dc.subject | deep learning | en_IE |
dc.subject | 2D | en_IE |
dc.subject | 3D | en_IE |
dc.subject | LWIR | en_IE |
dc.title | Generating thermal image data samples using 3D facial modelling techniques and deep learning methodologies | en_IE |
dc.type | Conference Paper | en_IE |
dc.date.updated | 2021-05-24T09:47:45Z | |
dc.identifier.doi | 10.1109/qomex48832.2020.9123079 | |
dc.local.publishedsource | https://doi.org/10.1109/qomex48832.2020.9123079 | en_IE |
dc.description.peer-reviewed | peer-reviewed | |
dc.contributor.funder | Horizon 2020 | en_IE |
dc.internal.rssid | 25993307 | |
dc.local.contact | Muhammad Ali Farooq. Email: m.farooq3@nuigalway.ie | |
dc.local.copyrightchecked | Yes | |
dc.local.version | ACCEPTED | |
dcterms.project | info:eu-repo/grantAgreement/EC/H2020::ECSEL-RIA/826131/EU/tHErmaL vIsion AUgmented awarenesS/HELIAUS | en_IE |
nui.item.downloads | 70 | |