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Section A

An approach to facial expression analysis with multi-model interactions

, , &
Pages 2329-2340 | Received 31 Jan 2013, Accepted 30 Apr 2013, Published online: 11 Jun 2013

References

  • C. Budayan, I. Dikmen, and M.T. Birgonul, Comparing the performance of traditional cluster analysis, self-organizing maps and fuzzy C-means method for strategic grouping, Expert Syst. Appl. 36(9) (2009), pp. 11772–11781. doi: 10.1016/j.eswa.2009.04.022
  • X.W. Chen and T. Huang, Facial expression recognition: A clustering-based approach, Pattern Recognit. Lett. 24(9–10) (2003), pp. 1295–1302. doi: 10.1016/S0167-8655(02)00371-9
  • A. Dhall, R. Goecke, S. Lucey, and T. Gedeon, Static facial expression analysis in tough conditions: Data, evaluation protocol and benchmark, IEEE International Conference on Computer Vision, Barcelona, Spain, 2011. IEEE, Piscataway, NJ, 2011, pp. 2106–2112. Available at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6114268.
  • P. Ekman and W.V. Friesen, Unmasking the Face: A Guide to Recognizing Emotions from Facial Expressions, Prentice Hall, Englewood Cliffs, NJ, 1975.
  • A. Ghahari, Y.R. Fatmehsari, and R.A. Zoroofi, A novel clustering-based feature extraction method for an automatic facial expression analysis system, in International Conference on Intelligent Information Hiding and Multimedia Signal, Kyoto, Japan, 2009, J.-S. Pan, Y.-W. Chen, and L.C. Jain, eds., IEEE Computer Society, Piscataway, NJ, 2009, pp. 1314–1317.
  • W. Gu, C. Xiang, Y.V. Venkatesh, D. Huang, and H. Lin, Facial expression recognition using radial encoding of local Gabor features and classifier synthesis, Pattern Recognit. 45(1) (2012), pp. 80–91. doi: 10.1016/j.patcog.2011.05.006
  • J. Hong, E.H. Suh, J. Kim, and S. Kim, Context-aware system for proactive personalized service based on context history, Expert Syst. Appl. 36(4) (2009), pp. 7448–7457. doi: 10.1016/j.eswa.2008.09.002
  • L. Jeni, A. Lorincz, T. Nagy, Z. Palotai, J. Sebok, Z. Szabo, and D. Takacs, 3D shape estimation in video sequences provides high precision evaluation of facial expressions, Image Vis. Comput. 30(10) (2012), pp. 785–795. doi: 10.1016/j.imavis.2012.02.003
  • L.A. Jeni, D. Takacs, and A. Lorincz, High-quality facial expression recognition in video streams using shape related information only, IEEE International Conference on Computer Vision Workshops, Barcelona, Spain, 2011, Piscataway, NJ, 2011, pp. 2168–2174. Available at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6114268.
  • M. Kyperountas, A. Tefas, and I. Pitas, Dynamic training using multistage clustering for face recognition, Pattern Recognit. 41(3) (2008), pp. 894–905. doi: 10.1016/j.patcog.2007.06.017
  • D. Liang, J. Yang, Z. Zheng, and Y. Chang, A facial expression recognition system based on supervised locally linear embedding, Pattern Recognit. Lett. 26(15) (2005), pp. 2374–2389. doi: 10.1016/j.patrec.2005.04.011
  • S. Liu, Q. Ruan, C. Wang, and G. An, Tensor rank one differential graph preserving analysis for facial expression recognition, Image Vis. Comput. 30(8) (2012), pp. 535–545. doi: 10.1016/j.imavis.2012.05.004
  • M. Matsugu, K. Mori, Y. Mitari, and Y. Kaneda, Subject independent facial expression recognition with robust face detection using a convolutional neural network, Neural Netw. 16(5–6) (2003), pp. 555–559. doi: 10.1016/S0893-6080(03)00115-1
  • A. Mian, Online learning from local features for video-based face recognition, Pattern Recognit. 44(5) (2011), pp. 1068–1075. doi: 10.1016/j.patcog.2010.12.001
  • P.Y. Mok, H.Q. Huang, Y.L. Kwok, and J.S. Au, A robust adaptive clustering analysis method for automatic identification of clusters, Pattern Recognit. 45(8) (2012), pp. 3017–3033. doi: 10.1016/j.patcog.2012.02.003
  • S. Nikitidis, A. Tefas, N. Nikolaidis, and I. Pitas, Subclass discriminant nonnegative matrix factorization for facial image analysis, Pattern Recognit. 45(12) (2012), pp. 4080–4091. doi: 10.1016/j.patcog.2012.04.030
  • B.Kr. Patra, S. Nandi, and P. Viswanath, A distance based clustering method for arbitrary shaped clusters in large datasets, Pattern Recognit. 44(12) (2011), pp. 2862–2870. doi: 10.1016/j.patcog.2011.04.027
  • L.F. Shang, J.C. Lv, and Z. Yi, Rigid medical image registration using PCA neural network, Neurocomputing 69(13–15) (2006), pp. 1717–1722. doi: 10.1016/j.neucom.2006.01.007
  • M. Sorci, G. Antonini, J. Cruz, T. Robin, M. Bierlaire, and J.P. Thiran, Modelling human perception of static facial expressions, Image Vis. Comput. 28(5) (2010), pp. 790–806. doi: 10.1016/j.imavis.2009.10.003
  • J. Sung and D. Kim, Real-time facial expression recognition using STAAM and layered GDA classifier, Image Vis. Comput. 27(9) (2009), pp. 1313–1325. doi: 10.1016/j.imavis.2008.11.010
  • H. Tang and T.S. Huang, 3D facial expression recognition based on automatically selected features, IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, Anchorage, USA, 2008. IEEE Computer Society, Piscataway, NJ, 2008, pp. 1–8. Available at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=4558053.
  • V. Vaidehi, K. Gayathri, and S. Vignesh, Efficient face detection and recognition using block independent component analysis and clustering, International Conference on Recent Trends in Information Technology, Chennai, India, 2011. IEEE Computer Society, Piscataway, NJ, 2011, pp. 561–566. Available at http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5972488
  • D. Wang, H.C. Lu, and X.L. Li, Two dimensional principal components of natural images and its application, Neurocomputing, 74(17) (2011), pp. 2745–2753. doi: 10.1016/j.neucom.2011.03.047
  • H. Wang and K.Q. Wang, Affective interaction based on person-independent facial expression space, Neurocomputing 71(10–12) (2008), pp. 1889–1901. doi: 10.1016/j.neucom.2007.10.022
  • C. Xu and Z. Feng, An affective modeling approach to interruptions in proactive computing environments, in International Conference on Human–Computer Interaction, Beijing, China, 2007, M.J. Dainoff, ed., Springer, Berlin, 2007, pp. 628–632.
  • W.K. Yang, C.Y. Sun, L. Zhang, and K. Ricanek, Laplacian bidirectional PCA for face recognition, Neurocomputing 74(1–3) (2010), pp. 487–493. doi: 10.1016/j.neucom.2010.08.020
  • Q. Zhang, S. Jeong, and M. Lee, Autonomous emotion development using incremental modified adaptive neuro-fuzzy inference system, Neurocomputing 86(1) (2012), pp. 33–44. doi: 10.1016/j.neucom.2011.12.034

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