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Random Forests for Real Time 3D Face Analysis

G. Fanelli, M. Dantone, J. Gall, A. Fossati and L. Van Gool
International Journal of Computer Vision
August 2012

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.


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@Article{eth_biwi_00957,
  author = {G. Fanelli and M. Dantone and J. Gall and A. Fossati and L. Van Gool},
  title = {Random Forests for Real Time 3D Face Analysis},
  journal = {International Journal of Computer Vision},
  year = {2012},
  month = {August},
  pages = {},
  volume = {},
  number = {},
  keywords = {Random forests; Head pose estimation; 3D facial features detection; Real time}
}