Graduate School and Research Center in Digital Sciences

Facial landmark detection on thermal data via fully annotated visible-to-thermal data synthesis

Mallat, Khawla; Dugelay, Jean-Luc

IJCB 2020, International Joint Conference on Biometrics, September 28–October 1, 2020 (Virtual Conference)

Thermal imaging has substantially evolved, during the recent years, to be established as a complement, or even occasionally as an alternative to conventional visible light imaging, particularly for face analysis applications. Facial landmark detection is a crucial prerequisite for facial image processing. Given the upswing of deep learning based approaches, the performance of facial landmark detection has been significantly improved. However, this uprise is merely limited to visible spectrum based face analysis tasks, as there are only few research works on facial landmark detection in thermal spectrum. This limitation is mainly due to the lack of available thermal face databases provided with full facial landmark annotations. In this paper, we propose to tackle this data shortage by converting existing face databases, designed for facial landmark detection task, from visible to thermal spectrum that will share the same provided facial landmark annotations. Using the synthesized thermal databases along with the facial landmark annotations, two different models are trained using active appearance models and deep alignment network. Evaluating the models trained on synthesized thermal data on real thermal data, we obtained facial landmark detection accuracy of 94.59% when tested on low quality thermal data and 95.63% when tested on high quality

Document Bibtex

Title:Facial landmark detection on thermal data via fully annotated visible-to-thermal data synthesis
Type:Conference
Language:English
City:Houston
Country:UNITED STATES
Date:
Department:Digital Security
Eurecom ref:6327
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Bibtex: @inproceedings{EURECOM+6327, year = {2020}, title = {{F}acial landmark detection on thermal data via fully annotated visible-to-thermal data synthesis}, author = {{M}allat, {K}hawla and {D}ugelay, {J}ean-{L}uc}, booktitle = {{IJCB} 2020, {I}nternational {J}oint {C}onference on {B}iometrics, {S}eptember 28\&\#8211;{O}ctober 1, 2020 ({V}irtual {C}onference)}, address = {{H}ouston, {UNITED} {STATES}}, month = {09}, url = {http://www.eurecom.fr/publication/6327} }
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