Thermal face recognition based on transformation by residual U-net and pixel shuffle upsampling

Soumya Chatterjee, Wei Ta Chu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a thermal face recognition system that first transforms the given face in the thermal spectrum into the visible spectrum, and then recognizes the transformed face by matching it with the face gallery. To achieve high-fidelity transformation, the U-Net structure with a residual network backbone is developed for generating visible face images from thermal face images. Our work mainly improves upon previous works on the Nagoya University thermal face dataset. In the evaluation, we show that the rank-1 recognition accuracy can be improved by more than 10%. The improvement on visual quality of transformed faces is also measured in terms of PSNR (with 0.36 dB improvement) and SSIM (with 0.07 improvement).

Original languageEnglish
Title of host publicationMultiMedia Modeling - 26th International Conference, MMM 2020, Proceedings
EditorsWen-Huang Cheng, Junmo Kim, Jung-Woo Choi, Wei-Ta Chu, Peng Cui, Min-Chun Hu, Wesley De Neve
PublisherSpringer
Pages679-689
Number of pages11
ISBN (Print)9783030377304
DOIs
Publication statusPublished - 2020 Jan 1
Event26th International Conference on MultiMedia Modeling, MMM 2020 - Daejeon, Korea, Republic of
Duration: 2020 Jan 52020 Jan 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11961 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on MultiMedia Modeling, MMM 2020
CountryKorea, Republic of
CityDaejeon
Period20-01-0520-01-08

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Chatterjee, S., & Chu, W. T. (2020). Thermal face recognition based on transformation by residual U-net and pixel shuffle upsampling. In W-H. Cheng, J. Kim, J-W. Choi, W-T. Chu, P. Cui, M-C. Hu, & W. De Neve (Eds.), MultiMedia Modeling - 26th International Conference, MMM 2020, Proceedings (pp. 679-689). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11961 LNCS). Springer. https://doi.org/10.1007/978-3-030-37731-1_55