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Human position and head direction tracking in fisheye camera using randomized ferns and fisheye histograms of oriented gradients

  • Veerachart SrisamosornEmail author
  • Noriaki Kuwahara
  • Atsushi Yamashita
  • Taiki Ogata
  • Shouhei Shirafuji
  • Jun Ota
Original Article

Abstract

This paper proposes a system for tracking human position and head direction using fisheye camera mounted to the ceiling. This is believed to be the first system to estimate head direction from ceiling-mounted fisheye camera. Fisheye histograms of oriented gradients descriptor is developed as a substitute to the histograms of oriented gradients descriptor which has been widely used for human detection in perspective camera. Human body and head are detected by the proposed descriptor and tracked to extract head area for direction estimation. Direction estimation using randomized ferns is adapted to work with fisheye images by using the proposed descriptor, guided by the direction of movement. With experiments on available dataset and new dataset with ground truth, the direction can be estimated with average error below \(40^{\circ }\), with head position error half of the head size.

Keywords

Human tracking Fisheye camera Video surveillance Head direction estimation 

Notes

Funding

This work was partially supported by JSPS KAKENHI (Grant Number 15H01698).

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflict of interest.

Supplementary material

Supplementary material 1 (mp4 14768 KB)

Supplementary material 2 (mp4 41017 KB)

Supplementary material 3 (mp4 40135 KB)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Precision Engineering, School of EngineeringThe University of TokyoTokyoJapan
  2. 2.Graduate School of Science and TechnologyKyoto Institute of TechnologyKyotoJapan
  3. 3.Department of Computer Science, School of ComputingTokyo Institute of TechnologyTokyoJapan
  4. 4.Research Into Artifacts, Center for Engineering (RACE), School of EngineeringThe University of TokyoTokyoJapan

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