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Nose Based Rigid Face Tracking

  • Luan P. e SilvaEmail author
  • Flávio H. de B. Zavan
  • Olga R. P. Bellon
  • Luciano Silva
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11401)

Abstract

Face detection is one of the first stages of face recognition systems. Thanks to advances in deep neural networks, success has been achieved on many similar image recognition tasks. When videos are available, temporal information can be used for determining the position of the face, avoiding having to detect faces for all frames. Such techniques can be applied in in-the-wild environments where current face detection methods fail to perform robustly. To address these limitations, this work explores an original approach, tracking the nose region initialized based on face quality analysis. A quality score is calculated for assisting the nose tracking initialization, avoiding depending on the first frame, in which may contain degraded data. The nose region, rather than the entire face was chosen due to it being unlikely to be occluded, being mostly invariant to facial expressions, and being visible in a long range of head poses. Experiments performed on the 300 Videos in the Wild and Point and Shoot Challenge datasets indicate nose tracking is a useful approach for in-the-wild scenarios.

Notes

Acknowledgements

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Universidade Federal do ParanáCuritibaBrazil

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