• DocumentCode
    247752
  • Title

    Depth-based face recognition using local quantized patterns adapted for range data

  • Author

    Mantecon, Tomas ; del-Bianco, Carlos R. ; Jaureguizar, Fernando ; Garcia, Narciso

  • Author_Institution
    Grupo de Tratamiento de Imagenes, Univ. Politec. de Madrid, Madrid, Spain
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    293
  • Lastpage
    297
  • Abstract
    A depth-based face recognition algorithm specially adapted to high range resolution data acquired by the new Microsoft Kinect 2 sensor is presented. A novel descriptor called Depth Local Quantized Pattern descriptor has been designed to make use of the extended range resolution of the new sensor. This descriptor is a substantial modification of the popular Local Binary Pattern algorithm. One of the main contributions is the introduction of a quantification step, increasing its capacity to distinguish different depth patterns. The proposed descriptor has been used to train and test a Support Vector Machine classifier, which has proven to be able to accurately recognize different people faces from a wide range of poses. In addition, a new depth-based face database acquired by the new Kinect 2 sensor have been created and made public to evaluate the proposed face recognition system.
  • Keywords
    face recognition; image classification; image resolution; image sensors; pose estimation; support vector machines; Microsoft Kinect 2 sensor; depth local quantized pattern descriptor; depth-based face database; depth-based face recognition algorithm; extended range resolution; local binary pattern algorithm; local quantized patterns; range data; support vector machine classifier; Databases; Face; Face recognition; Feature extraction; Histograms; Image resolution; Support vector machines; Depth Local Quantized Pattern; Kinect 2; classification; face database; face recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025058
  • Filename
    7025058