Human intention detection with facial expressions using video analytics

  • Authors

    • K Prema
    • L Leema Priyadharshini
    • C Shyamala Kumari
    • S Florence
    2018-03-10
    https://doi.org/10.14419/ijet.v7i2.4.10032
  • Feature Tracker, Facial Expressions, Support Vector Machines, Emotion Classification.

  • 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.

  • References

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      [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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  • How to Cite

    Prema, K., Leema Priyadharshini, L., Shyamala Kumari, C., & Florence, S. (2018). Human intention detection with facial expressions using video analytics. International Journal of Engineering & Technology, 7(2.4), 14-16. https://doi.org/10.14419/ijet.v7i2.4.10032