• DocumentCode
    25094
  • Title

    Random Cascaded-Regression Copse for Robust Facial Landmark Detection

  • Author

    Zhen-Hua Feng ; Huber, Patrik ; Kittler, Josef ; Christmas, William ; Xiao-Jun Wu

  • Author_Institution
    Sch. of IoT Eng., Jiangnan Univ., Wuxi, China
  • Volume
    22
  • Issue
    1
  • fYear
    2015
  • fDate
    Jan. 2015
  • Firstpage
    76
  • Lastpage
    80
  • Abstract
    In this letter, we present a random cascaded-regression copse (R-CR-C) for robust facial landmark detection. Its key innovations include a new parallel cascade structure design, and an adaptive scheme for scale-invariant shape update and local feature extraction. Evaluation on two challenging benchmarks shows the superiority of the proposed algorithm to state-of-the-art methods.
  • Keywords
    face recognition; object detection; regression analysis; adaptive scheme; local feature extraction; parallel cascade structure design; random cascaded-regression copse; robust facial landmark detection; scale-invariant shape update; Accuracy; Educational institutions; Face; Feature extraction; Robustness; Shape; Training; Adaptive shape update; R-CR-C; cascaded regression; facial landmark detection;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2014.2347011
  • Filename
    6877655
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=25094