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

Authors(2) :-B. Sriharika, B. Anuradha

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.
B. Sriharika, B. Anuradha
Face recognition, Illumination, Non Uniform Blurring, Convolution Model, ESL-CSMP Technique
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Publication Details
  Published in : Volume 4 | Issue 7 | March-April 2018
  Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 08-14
Manuscript Number : IJSRST21841357
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
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), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 7, pp.08-14, March-April-2018
URL : http://ijsrst.com/IJSRST21841357