• DocumentCode
    940979
  • Title

    Audio-Visual Biometrics

  • Author

    Aleksic, Petar S. ; Katsaggelos, Aggelos K.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Northwestern Univ., Evanston, IL
  • Volume
    94
  • Issue
    11
  • fYear
    2006
  • Firstpage
    2025
  • Lastpage
    2044
  • Abstract
    Biometric characteristics can be utilized in order to enable reliable and robust-to-impostor-attacks person recognition. Speaker recognition technology is commonly utilized in various systems enabling natural human computer interaction. The majority of the speaker recognition systems rely only on acoustic information, ignoring the visual modality. However, visual information conveys correlated and complimentary information to the audio information and its integration into a recognition system can potentially increase the system´s performance, especially in the presence of adverse acoustic conditions. Acoustic and visual biometric signals, such as the person´s voice and face, can be obtained using unobtrusive and user-friendly procedures and low-cost sensors. Developing unobtrusive biometric systems makes biometric technology more socially acceptable and accelerates its integration into every day life. In this paper, we describe the main components of audio-visual biometric systems, review existing systems and their performance, and discuss future research and development directions in this area
  • Keywords
    acoustics; biometrics (access control); face recognition; feature extraction; man-machine systems; speech recognition; acoustic information; audio-visual biometrics; feature extraction; natural human computer interaction; person recognition; speaker recognition technology; visual information; visual modality; Acceleration; Acoustic sensors; Biometrics; Biosensors; Character recognition; Human computer interaction; Research and development; Robustness; Speaker recognition; System performance; Audio-visual biometrics; audio-visual databases; audio-visual fusion; audio-visual person recognition; face tracking; hidden Markov models; multimodal recognition; visual feature extraction;
  • fLanguage
    English
  • Journal_Title
    Proceedings of the IEEE
  • Publisher
    ieee
  • ISSN
    0018-9219
  • Type

    jour

  • DOI
    10.1109/JPROC.2006.886017
  • Filename
    4052464