iFR: interactively pose corrected face recognition

Simon Nash, Mark Rhodes, Joanna Isabelle Olszewska

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

Abstract

Although face recognition applications are growing, robust face recognition is still a challenging task due e.g. to variations on face poses, facial expressions, or lighting conditions. In this paper, we propose a new method which allows both automatic face detection and recognition and incorporates an interactive selection of facial features in conjunction with our new pose-correction algorithm. Our resulting system we call iFR successfully recognizes faces across pose, while being computationally efficient and outperforming standard approaches, as demonstrated in tests carried out on publicly available standard datasets.
Original languageEnglish
Title of host publicationProceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies
Subtitle of host publicationBIOSIGNALS, (BIOSTEC 2016)
Pages106-112
Number of pages7
Volume4
DOIs
Publication statusPublished - 23 Feb 2016
Externally publishedYes
Event9th International Joint Conference on Biomedical Engineering Systems and Technologies - Rome, Italy
Duration: 21 Feb 201623 Feb 2016
Conference number: 9
http://www.biostec.org/?y=2016

Conference

Conference9th International Joint Conference on Biomedical Engineering Systems and Technologies
Abbreviated titleBIOSTEC 2016
CountryItaly
CityRome
Period21/02/1623/02/16
Internet address

Keywords

  • Face Detection
  • Face Recognition
  • AdaBoost
  • Template
  • Facial Features
  • Eigenfaces
  • Pose Correction
  • Human-Computer Interactive Systems

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  • Cite this

    Nash, S., Rhodes, M., & Olszewska, J. I. (2016). iFR: interactively pose corrected face recognition. In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies: BIOSIGNALS, (BIOSTEC 2016) (Vol. 4, pp. 106-112) https://doi.org/10.5220/0005857801060112