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Memorias de investigación
Communications at congresses:
Depth-Based Face Recognition using Local Quantized Patterns Adapted for Range Data
Year:2014
Research Areas
  • Electronic technology and of the communications
Information
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.
International
Si
Congress
IEEE Int. Conf. on Image Processing, ICIP 2014
960
Place
Paris, France
Reviewers
Si
ISBN/ISSN
1522-4880
10.1109/ICIP.2014.7025058
Start Date
27/10/2014
End Date
30/10/2014
From page
293
To page
297
Depth-Based Face Recognition using Local Quantized Patterns Adapted for Range Data
Participants
  • Autor: Tomas Mantecon Del Valle (UPM)
  • Autor: Carlos Roberto del Blanco Adan (UPM)
  • Autor: Fernando Jaureguizar Nuñez (UPM)
  • Autor: Narciso Garcia Santos (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Tratamiento de Imágenes (GTI)
  • Departamento: Señales, Sistemas y Radiocomunicaciones
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