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Face Detection and Expression Recognition Using Haar Cascade Classifier and Fisherface Algorithm

  • Indrasom GangopadhyayEmail author
  • Anulekha Chatterjee
  • Indrajit Das
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 922)

Abstract

Facial expression recognition is the process of identifying the expression that is displayed by a person, and it has several applications in the fields of medicine, human–computer interaction others; where recognition of expressions displayed on a face is of vital. The process mainly comprises face detection and expression recognition using Haar classifier and using Fisherface based on Fisher’s linear discriminant analysis (FLDA) for dimensionality reduction, respectively. The dataset from which the faces were presented to the classifiers yielded a precision of 96.3% with a recognition speed of 8.2 s. An improvement in recognition accuracy of 3.4% is observed by this algorithm from other algorithms, viz. eigenfaces, LBPH recognizer, and artificial neural network; although with a drawback of incorrect recognition in cases of uneven illumination or low-light conditions. This result may be considered as efficient both with respect to accuracy and speed of recognition of the facial expressions.

Keywords

Haar cascade classifier Fisherface Cohn-Kanade database Facial expression recognition Face detection 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Indrasom Gangopadhyay
    • 1
    Email author
  • Anulekha Chatterjee
    • 1
  • Indrajit Das
    • 1
  1. 1.Meghnad Saha Institute of TechnologyKolkataIndia

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