Human intention detection with facial expressions using video analytics

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    The manuscript should contain an abstract. The abstract should be self-contained and citation-free and should not exceed 200 words. The abstract should state the purpose, approach, results and conclusions of the work.The author should assume that the reader has some knowledge of the subject but has not read the paper. Thus, the abstract should be intelligible and complete in it-self (no numerical references); it should not cite figures, tables, or sections of the paper. The abstract should be written using third person instead of first person.


  • Keywords


    Feature Tracker; Facial Expressions; Support Vector Machines; Emotion Classification.

  • References


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      [9] J. F. Cohn, A. J. Zlochower, J. J. Lien, and T. Kanade. Automated face analysis by feature point tracking has high concurrent validity with manual faces coding. Psychophysiology, 36:35–43, 1999.https://doi.org/10.1017/S0048577299971184.

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      [15] T. Joachims. Text categorization with support vector machines: Learning with many relevant features. In Proceedings of ECML-98, 10th European Conference on Machine Learning, pages 137–142, Heidelberg, DE, 1998. Springer Verlag.

      [16] T. Kanade, J. Cohn, and Y. Tian. Comprehensive database for facial expression analysis. In Proceedings of the 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG’00), pages 46–53, 2000.https://doi.org/10.1109/AFGR.2000.840611.


 

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Article ID: 10032
 
DOI: 10.14419/ijet.v7i2.4.10032




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