Head-Pose Estimation In-the-Wild Using a Random Forest

  • Roberto Valle
  • José Miguel Buenaposada
  • Antonio Valdés
  • Luis Baumela
Conference paper

DOI: 10.1007/978-3-319-41778-3_3

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9756)
Cite this paper as:
Valle R., Buenaposada J.M., Valdés A., Baumela L. (2016) Head-Pose Estimation In-the-Wild Using a Random Forest. In: Perales F., Kittler J. (eds) Articulated Motion and Deformable Objects. AMDO 2016. Lecture Notes in Computer Science, vol 9756. Springer, Cham

Abstract

Human head-pose estimation has attracted a lot of interest because it is the first step of most face analysis tasks. However, many of the existing approaches address this problem in laboratory conditions. In this paper, we present a real-time algorithm that estimates the head-pose from unrestricted 2D gray-scale images. We propose a classification scheme, based on a Random Forest, where patches extracted randomly from the image cast votes for the corresponding discrete head-pose angle. In the experiments, the algorithm performs similar and better than the state-of-the-art in controlled and in-the-wild databases respectively.

Keywords

Head-pose estimation Random forest Real-time In-the-wild 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Roberto Valle
    • 1
  • José Miguel Buenaposada
    • 2
  • Antonio Valdés
    • 3
  • Luis Baumela
    • 1
  1. 1.Univ. Politécnica MadridMadridSpain
  2. 2.Univ. Rey Juan CarlosMóstolesSpain
  3. 3.Univ. Complutense MadridMadridSpain

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