• DocumentCode
    3151486
  • Title

    Limitation investigation toward lips recognition

  • Author

    Liu, Yun-Fu ; Lin, Chao-Yu ; Guo, Jing-Ming

  • Author_Institution
    Dept. of Electr. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
  • fYear
    2012
  • fDate
    25-30 March 2012
  • Firstpage
    1857
  • Lastpage
    1860
  • Abstract
    In this paper, the impact of the lips for facial recognition is investigated. In the first stage of the proposed system, a Fast Box Filtering (FBF) is proposed to generate a noise-free source with high processing efficiency. Afterward, five various mouth corners are detected though the proposed system, in which it is also able to resist beard and rotation problems. For the feature extraction, two geometric ratios and 10 parabolic related parameters are adopted for further recognition through the Support Vector Machine (SVM). Experimental results demonstrate that when the number of subjects is fewer or equal to 36, the Correct Accept Rate (CAR) is greater than 98%, and the False Accept Rate (FAR) is smaller than 0.064% (CAR>;95.6%, FAR<;0.083%| #Subjects ≤ 54). Moreover, the processing speed of the overall system achieves 34.43 fps (frame/sec) which meets the real-time requirement.
  • Keywords
    face recognition; filtering theory; support vector machines; CAR; FAR; FBF; SVM; correct accept rate; facial recognition; false accept rate; fast box filtering; lips recognition; parabolic related parameters; support vector machine; Erbium; Face recognition; Feature extraction; Filtering; Gray-scale; Lips; Mouth; Lips recognition; feature extraction; lips analysis; lips detection; pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
  • Conference_Location
    Kyoto
  • ISSN
    1520-6149
  • Print_ISBN
    978-1-4673-0045-2
  • Electronic_ISBN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2012.6288264
  • Filename
    6288264