Abstract / truncated to 115 words (read the full abstract)

Thermal imaging technology has significantly evolved during the last couple of decades, mostly thanks to thermal cameras having become more affordable and user friendly. However, and given that the exploration of thermal imagery is reasonably new, only a few public databases are available to the research community. This limitation consequently prevents the impact of deep learning technologies from generating improved and reliable face biometric systems that operate in the thermal spectrum. A possible solution relates to the development of technologies that bridge the gap between the visible and thermal spectrum. In attempting to respond to this necessity, the research presented in this dissertation aims to explore interspectral synthesis as a direction for efficient and prompt ... toggle 6 keywords

thermal imagery interspectral synthesis biometrics face recognition facial landmark detection deep learning

Information

Author
Mallat, Khawla
Institution
EURECOM
Supervisor
Publication Year
2020
Upload Date
Jan. 15, 2021

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