Graduate School and Research Center in Digital Sciences

Multi-variation visible and thermal face database for cross-spectrum face recognition

Mallat, Khawla; Dugelay, Jean-Luc

BIOSIG 2018, 17th International Conference of the Biometrics Special Interest Group, 26-29 September 2018, Darmstadt, Germany

Best Poster Award

Although visible face recognition systems have grown as a major area of research, they are still facing serious challenges when operating in uncontrolled environments. In attempt to overcome these limitations, thermal imagery has been investigated as a promising direction to extend face recognition technology. However, the reduced number of databases acquired in thermal spectrum limits its exploration. In this paper, we introduce a database of face images acquired simultaneously in visible and thermal spectra under various variations: illumination, expression, pose and occlusion. Then, we present a comparative study of face recognition performances on both modalities against each variation and the impact of bimodal fusion. We prove that thermal spectrum rivals with the visible spectrum not only in the presence of illumination changes, but also in case of expression and poses changes.

Document Bibtex

Title:Multi-variation visible and thermal face database for cross-spectrum face recognition
Keywords:thermal spectrum, visible spectrum, face database, illumination, expression, pose, occlusion, sensor-level fusion, score-level fusion
Department:Digital Security
Eurecom ref:5700
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Bibtex: @inproceedings{EURECOM+5700, year = {2018}, title = {{M}ulti-variation visible and thermal face database for cross-spectrum face recognition}, author = {{M}allat, {K}hawla and {D}ugelay, {J}ean-{L}uc}, booktitle = {{BIOSIG} 2018, 17th {I}nternational {C}onference of the {B}iometrics {S}pecial {I}nterest {G}roup, 26-29 {S}eptember 2018, {D}armstadt, {G}ermany}, address = {{D}armstadt, {GERMANY}}, month = {09}, url = {} }
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