Temporal similarity analysis of remote photoplethysmography for fast 3D mask face presentation attack detection

Si Qi Liu, Xiangyuan LAN, Pong Chi YUEN

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

To tackle the 3D mask face presentation attack, remote Photoplethysmography (rPPG), a biomedical technique that can detect heartbeat signal remotely, is employed as an intrinsic liveness cue. Although existing rPPG-based methods exhibit encouraging results, they require long observation time (10-12 seconds) to identify the heartbeat information, which limits their employment in real applications such as smartphone unlock and e-payment. To shorten the observation time (within 1-second) while keeping the performance, we propose a fast rPPG-based 3D mask presentation attack detection (PAD) method by analyzing the similarity of local facial rPPG signals in the time domain. In particular, a set of temporal similarity features of facial and background local rPPG signals are designed and fused to adapt the real world variations based on rPPG shape and phase properties. For better evaluation under practical variations, we build the HKBU-MARsV2+ dataset that includes 16 masks from 2 types and 6 lighting conditions. Finally, extensive experiments are conducted on 11092 shortterm video slots from 4 datasets with a large number of real- world variations, in terms of mask type, lighting condition, camera, resolution of face region, and compression setting. Results show that the proposed TSrPPG outperforms the state-of-the-art competitors dramatically on discriminabil- ity and generalizability. To our best knowledge, this is the first work that addresses the length of observation time issue of rPPG-based 3D mask PAD.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2597-2605
Number of pages9
ISBN (Electronic)9781728165530
DOIs
Publication statusPublished - Mar 2020
Event2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020 - Snowmass Village, United States
Duration: 1 Mar 20205 Mar 2020

Publication series

NameProceedings - 2020 IEEE Winter Conference on Applications of Computer Vision, WACV 2020

Conference

Conference2020 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2020
Country/TerritoryUnited States
CitySnowmass Village
Period1/03/205/03/20

Scopus Subject Areas

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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