A Parametric Study of Deep Perceptual Model on Visible to Thermal Face Recognition

Wei Ta Chu, Jo Ning Wu

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

2 Citations (Scopus)

Abstract

Recently deep perceptual mapping (DPM) based on auto-encoder provides the state-the-art thermal to visible face recognition. Features extracted from patches of a long-wave infra-red (LWIR) face image are transformed into a space by an auto-encoder, such that features from infra-red images are comparable with features from visible images. In this paper, we comprehensively evaluate DPM with different settings, in order to build a reference study for future research.

Original languageEnglish
Title of host publicationVCIP 2018 - IEEE International Conference on Visual Communications and Image Processing
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538644584
DOIs
Publication statusPublished - 2018 Jul 2
Event33rd IEEE International Conference on Visual Communications and Image Processing, VCIP 2018 - Taichung, Taiwan
Duration: 2018 Dec 92018 Dec 12

Publication series

NameVCIP 2018 - IEEE International Conference on Visual Communications and Image Processing

Conference

Conference33rd IEEE International Conference on Visual Communications and Image Processing, VCIP 2018
CountryTaiwan
CityTaichung
Period18-12-0918-12-12

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing

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