International Journal of Computer Vision

, Volume 101, Issue 3, pp 437–458

Random Forests for Real Time 3D Face Analysis

  • Gabriele Fanelli
  • Matthias Dantone
  • Juergen Gall
  • Andrea Fossati
  • Luc Van Gool
Article

Abstract

We present a random forest-based framework for real time head pose estimation from depth images and extend it to localize a set of facial features in 3D. Our algorithm takes a voting approach, where each patch extracted from the depth image can directly cast a vote for the head pose or each of the facial features. Our system proves capable of handling large rotations, partial occlusions, and the noisy depth data acquired using commercial sensors. Moreover, the algorithm works on each frame independently and achieves real time performance without resorting to parallel computations on a GPU. We present extensive experiments on publicly available, challenging datasets and present a new annotated head pose database recorded using a Microsoft Kinect.

Keywords

Random forests Head pose estimation 3D facial features detection Real time 

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Gabriele Fanelli
    • 1
  • Matthias Dantone
    • 1
  • Juergen Gall
    • 2
  • Andrea Fossati
    • 1
  • Luc Van Gool
    • 1
    • 3
  1. 1.Computer Vision LaboratoryETH ZurichZurichSwitzerland
  2. 2.Perceiving Systems DepartmentMax Planck Institute for Intelligent SystemsTübingenGermany
  3. 3.Department of Electrical Engineering/IBBTK.U. LeuvenHeverleeBelgium

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