Thermal Face Recognition Based on Multi-scale Image Synthesis

Wei Ta Chu, Ping Shen Huang

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

Abstract

We present a transformation-based method to achieve thermal face recognition. Given a thermal face, the proposed model transforms the input to a synthesized visible face, which is then used as a probe to compare with visible faces in the database. This transformation model is built on the basis of a generative adversarial network, mainly with the ideas of multi-scale discrimination and various loss functions like feature embedding, identity preservation, and facial landmark-guided texture synthesis. The evaluation results show that the proposed method outperforms the state of the art.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 27th International Conference, MMM 2021, Proceedings
EditorsJakub Lokoc, Tomáš Skopal, Klaus Schoeffmann, Vasileios Mezaris, Xirong Li, Stefanos Vrochidis, Ioannis Patras
PublisherSpringer Science and Business Media Deutschland GmbH
Pages99-110
Number of pages12
ISBN (Print)9783030678319
DOIs
Publication statusPublished - 2021
Event27th International Conference on MultiMedia Modeling, MMM 2021 - Prague, Czech Republic
Duration: 2021 Jun 222021 Jun 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12572 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference27th International Conference on MultiMedia Modeling, MMM 2021
Country/TerritoryCzech Republic
CityPrague
Period21-06-2221-06-24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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