A Novel Approach for Facial Emotion Recognition Based On Kernel Extreme Sparse Learning with CSMP

Authors

  • B. Sriharika  M.Tech Student, Department of ECE, Svuce, Tirupati, Andhra Pradesh, India
  • B. Anuradha  Professor, Department Ofece, SVUCE, Tirupati, Andhra Pradesh, India

Keywords:

Face recognition, Illumination, Non Uniform Blurring, Convolution Model, ESL-CSMP Technique

Abstract

Camera motion during light exposure causes image blur and disturbs them. The nonuniform blur occurring due to camera inclination and rotations cannot be handled efficiently .The traditional methods depending on the convolution model are failed in case non-uniform blur. Here we recommend a procedure for face recognition with space-varying motion blur. To deal with it NU-MOB algorithm is used. A set of determined gallery image is blurred and the input probe image is compared with each image to find closest match. Our future work is based on the emotion identification where considering the different emotion based videos and the emotion recognition performed using the ESL-CSMP technique. And improve performance by using kernels in ESL method. Experimental results prove to be better and yields better performance when compared to the other state of art methods.

References

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International Journal of Scientific Research in Science and Technology

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Published

2018-02-28

Issue

Volume 4, Issue 7, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
B. Sriharika, B. Anuradha, " A Novel Approach for Facial Emotion Recognition Based On Kernel Extreme Sparse Learning with CSMP, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 7, pp.08-14, March-April-2018.