Open Access
MATEC Web of Conferences
Volume 54, 2016
2016 7th International Conference on Mechanical, Industrial, and Manufacturing Technologies (MIMT 2016)
Article Number 05001
Number of page(s) 5
Section Computer information science and Its Applications
Published online 22 April 2016
  1. F. Ahmad, A. Najam, & Z. Ahmed, Image-based Face detection and recognition: “State of the art”, IJCSI International Journal of Computer Science Issues, 9, issue 6, no. 1, 169–172, (2012). [Google Scholar]
  2. G. Dashore, & V.C.Raj, An efficient method for face recognition using principal component analysis. International Journal of Advanced Technnology & Engineering Research, II, 2, 23–28, (2012). [Google Scholar]
  3. P. V Saudagare & D. S.Chaudhari, “Facial expression recognition using neural network–An overview”, International Journal of Soft Computing and Engineering (IJSCE), 2, 1, 224–227, (2012). [Google Scholar]
  4. D. L. Baggio, et al., Mastering OpenCV with Practical Computer Vision Projects. Packt Publishing, (2012). [Google Scholar]
  5. B. Jiang, M. F. Valstar, MartinezB., and M. Pantic, “A dynamic appearance descriptor approach to facial actions temporal modelling”, IEEE Transactions of Systems, Man and Cybernetics-Part B, 44, 2, 161–174, (2011 and 2014). [Google Scholar]
  6. X. Tan and B. Triggs, “Enhanced local texture feature sets for face recognition under difficult lighting conditions,“ IEEE Transactions on Image Processing, 19, 1635–1650, (2010). [CrossRef] [Google Scholar]
  7. M. F. Valstar and M. Pantic, “Fully automatic recognition of the temporal phases of facial actions”, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42, 1, pp. 28–43, (2012). [CrossRef] [Google Scholar]
  8. B. Jiang, M. F. Valstar, & M. Pantic, “Action Unit detection using sparse appearance descriptors in space-time video volumes”, IEEE Int’l. Conf. Face and Gesture Recognition (FG’11), 314–321, March (2011). [Google Scholar]
  9. T. R. Almaev & M. F. Valstar, “Local gabor binary patterns from three orthogonal planes for automatic facial expression recognition”, Proc. Affective Computing and Intelligent Interaction, 356–361, (2013). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.