Preliminary results on nonparametric facial occlusion detection

• LÓPEZ SÁNCHEZ, Daniel ^[2] ; GONZÁLEZ ARRIETA, Angélica ^[1]
  1. [1] Universidad de Salamanca

     Universidad de Salamanca

     Salamanca, España

     
  2. [2] ACM Member
• Localización: ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, ISSN-e 2255-2863, Vol. 5, Nº. 1, 2016, págs. 51-61
• Idioma: inglés
• DOI: 10.14201/ADCAIJ2016515161
• Enlaces
  • Texto completo
• Resumen

  • The problem of face recognition has been extensively studied in the available literature, however, some aspects of this field require further research. The design and implementation of face recognition systems that can efficiently handle unconstrained conditions (e.g. pose variations, illumination, partial occlusion...) is still an area under active research. This work focuses on the design of a new nonparametric occlusion detection technique. In addition, we present some preliminary results that indicate that the proposed technique might be useful to face recognition systems, allowing them to dynamically discard occluded face parts.

• Referencias bibliográficas
  • Ekenel, H. K., 2009. A robust face recognition algorithm for real-world applications. Ph.D. thesis, Karlsruhe, Univ., Diss., 2009.
  • Hughes, G. P., 1968. On the mean accuracy of statistical pattern recognizers. Information Theory, IEEE Transactions on, 14(1):55–63.
  • Jia, H. and Martinez, A. M., 2008. Face recognition with occlusions in the training and testing sets. In Automatic Face & Gesture Recognition,...
  • http://dx.doi.org/10.1109/afgr.2008.4813410
  • Kazemi, V. and Sullivan, J., 2014. One millisecond face alignment with an ensemble of regression trees. In Proceedings of the IEEE Conference...
  • http://dx.doi.org/10.1109/cvpr.2014.241
  • King, D. E., 2009. Dlib-ml: A Machine Learning Toolkit. Journal of Machine Learning Research, 10:1755–1758.
  • Liu, J., Deng, Y., and Huang, C., 2015. Targeting ultimate accuracy: Face recognition via deep embedding. arXiv preprint arXiv:1506.07310.
  • Martinez, A. M., 1998. The AR face database. CVC Technical Report, 24.
  • Martínez, A. M., 2002. Recognizing imprecisely localized, partially occluded, and expression variant faces from a single sample per class....
  • Min, R., Hadid, A., and Dugelay, J.-L., 2011. Improving the recognition of faces occluded by facial accessories. In Automatic Face & Gesture...
  • http://dx.doi.org/10.1109/fg.2011.5771439
  • Murphy, K. P., 2012. Machine learning: a probabilistic perspective. MIT press.
  • Ojala, T., Pietikäinen, M., and Harwood, D., 1996. A comparative study of texture measures with classification based on featured distributions....
  • http://dx.doi.org/10.1016/0031-3203(95)00067-4
  • Ojala, T., Pietikäinen, M., and Mäenpää, T., 2002. Multiresolution gray-scale and rotation invariant texture classification with local binary...
  • Tan, X., Chen, S., Zhou, Z.-H., and Zhang, F., 2005. Recognizing partially occluded, expression variant faces from single training image per...