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    • Keywords


      Emotion recognition; eigenvalue; Levenberg–Marquardt algorithm; neural network; classification

    • Abstract


      In this paper, a simple and computationally efficient approach is proposed for person independent facial emotion recognition. The proposed approach is based on the significant features of an image, i.e., the collection of few largest eigenvalues (LE). Further, a Levenberg–Marquardt algorithm-based neural network (LMNN) is applied for multiclass emotions classification. This leads to a new facial emotion recognition approach (LE-LMNN) which is systematically examined on JAFFE and Cohn–Kanade databases. Experimental results illustrate that the LE-LMNN approach is effective and computationally efficient for facial emotion recognition. The robustness of the proposed approach is also tested on low-resolution facial emotion images.The performance of the proposed approach is found to be superior as compared to the various existing methods.

    • Author Affiliations



      1. Department of Electrical and Electronics Engineering, BITS Pilani, Dubai Campus, Dubai International Academic City, Dubai 34505, UAE
      2. Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee 247667, India
      3. Department of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology, University of Delhi, New Delhi 110078, India
    • Dates

  • Sadhana | News

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