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A New Learning-Based Boosting in Multiple Classifiers for Color Facial Expression Identification

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 509))

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Abstract

A new method for automatic color facial expression identification using multiple classifier classification system has been developed. The system is primarily composed of three classifiers. The same color face features are then trained independently using three different classifiers. Now, a super classification technique integrates the decisions coming from each single classifier which outcomes as a final identified expression. To fuse the conclusion drawn by different classifiers, we apply a new technique of learning-based boosting which improves the complete system performance meaningfully in terms of recognition accuracy.

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Authors and Affiliations

  1. Computer Science and Engineering Department, NIT, Durgapur, Mahatma Gandhi Avenue, Durgapur, 713209, West Bengal, India

    Dhananjoy Bhakta & Goutam Sarker

Authors
  1. Dhananjoy Bhakta
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  2. Goutam Sarker
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Corresponding author

Correspondence to Dhananjoy Bhakta .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Birla Institute of Technology Mesra, Ranchi, Jharkhand, India

    Sudip Kumar Sahana

  2. Department of Computer Science and Engineering, Birla Institute of Technology Mesra, Ranchi, Jharkhand, India

    Sujan Kumar Saha

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Bhakta, D., Sarker, G. (2017). A New Learning-Based Boosting in Multiple Classifiers for Color Facial Expression Identification. In: Sahana, S.K., Saha, S.K. (eds) Advances in Computational Intelligence. ICCI 2015. Advances in Intelligent Systems and Computing, vol 509. Springer, Singapore. https://doi.org/10.1007/978-981-10-2525-9_26

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  • DOI: https://doi.org/10.1007/978-981-10-2525-9_26

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2524-2

  • Online ISBN: 978-981-10-2525-9

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