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Improved Face Recognition across Poses using Fusion of Probabilistic Latent Variable Models.

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  • معلومة اضافية
    • Author-Supplied Keywords:
      classifier fusion
      face recognition
      pose
      probabilistic latent variable
      video
    • Abstract:
      Uncontrolled environments have often required face recognition systems to identify faces appearing in poses that are different from those of the enrolled samples. To address this problem, probabilistic latent variable models have been used to perform face recognition across poses. Although these models have demonstrated outstanding performance, it is not clear whether richer parameters always lead to performance improvement. This work investigates this issue by comparing performance of three probabilistic latent variable models, namely PLDA, TFA, and TPLDA, as well as the fusion of these classifiers on collections of video data. Experiments on the VidTIMIT+UMIST and the FERET datasets have shown that fusion of multiple classifiers improves face recognition across poses, given that the individual classifiers have similar performance. This proves that different probabilistic latent variable models learn statistical properties of the data that are complementary (not redundant). Furthermore, fusion across multiple images has also been shown to produce better perfomance than recogition using single still image. [ABSTRACT FROM AUTHOR]
    • Abstract:
      Copyright of Telkomnika is the property of Department of Electrical Engineering, Ahmad Dahlan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
    • Author Affiliations:
      1Department of Computer Science and Electronics, Universitas Gadjah Mada FMIPA Sekip Utara, Bulaksumur, Sleman, Yogyakarta, Indonesia
      2Science and Engineering Faculty, Queensland University of Technology, 2 George St, Brisbane CBD, Queensland, Australia
    • ISSN:
      1693-6930
    • Accession Number:
      10.12928/telkomnika.v16i1.5731
    • Accession Number:
      127677000
  • Citations
    • ABNT:
      WIBOWO, M. E. et al. Improved Face Recognition across Poses using Fusion of Probabilistic Latent Variable Models. Telkomnika, [s. l.], v. 15, n. 4, p. 1976–1986, 2017. DOI 10.12928/telkomnika.v16i1.5731. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=127677000&custid=s8280428. Acesso em: 23 fev. 2020.
    • AMA:
      Wibowo ME, Tjondronegoro D, Chandran V, Pulungan R, Istiyanto JE. Improved Face Recognition across Poses using Fusion of Probabilistic Latent Variable Models. Telkomnika. 2017;15(4):1976-1986. doi:10.12928/telkomnika.v16i1.5731.
    • APA:
      Wibowo, M. E., Tjondronegoro, D., Chandran, V., Pulungan, R., & Istiyanto, J. E. (2017). Improved Face Recognition across Poses using Fusion of Probabilistic Latent Variable Models. Telkomnika, 15(4), 1976–1986. https://doi.org/10.12928/telkomnika.v16i1.5731
    • Chicago/Turabian: Author-Date:
      Wibowo, Moh Edi, Dian Tjondronegoro, Vinod Chandran, Reza Pulungan, and Jazi Eko Istiyanto. 2017. “Improved Face Recognition across Poses Using Fusion of Probabilistic Latent Variable Models.” Telkomnika 15 (4): 1976–86. doi:10.12928/telkomnika.v16i1.5731.
    • Harvard:
      Wibowo, M. E. et al. (2017) ‘Improved Face Recognition across Poses using Fusion of Probabilistic Latent Variable Models’, Telkomnika, 15(4), pp. 1976–1986. doi: 10.12928/telkomnika.v16i1.5731.
    • Harvard: Australian:
      Wibowo, ME, Tjondronegoro, D, Chandran, V, Pulungan, R & Istiyanto, JE 2017, ‘Improved Face Recognition across Poses using Fusion of Probabilistic Latent Variable Models’, Telkomnika, vol. 15, no. 4, pp. 1976–1986, viewed 23 February 2020, .
    • MLA:
      Wibowo, Moh Edi, et al. “Improved Face Recognition across Poses Using Fusion of Probabilistic Latent Variable Models.” Telkomnika, vol. 15, no. 4, Dec. 2017, pp. 1976–1986. EBSCOhost, doi:10.12928/telkomnika.v16i1.5731.
    • Chicago/Turabian: Humanities:
      Wibowo, Moh Edi, Dian Tjondronegoro, Vinod Chandran, Reza Pulungan, and Jazi Eko Istiyanto. “Improved Face Recognition across Poses Using Fusion of Probabilistic Latent Variable Models.” Telkomnika 15, no. 4 (December 2017): 1976–86. doi:10.12928/telkomnika.v16i1.5731.
    • Vancouver/ICMJE:
      Wibowo ME, Tjondronegoro D, Chandran V, Pulungan R, Istiyanto JE. Improved Face Recognition across Poses using Fusion of Probabilistic Latent Variable Models. Telkomnika [Internet]. 2017 Dec [cited 2020 Feb 23];15(4):1976–86. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=127677000&custid=s8280428