Real Time Facial Emotion Recognition based on Image Processing and Machine Learning

  title={Real Time Facial Emotion Recognition based on Image Processing and Machine Learning},
  author={Rituparna Halder and Sushmita Sengupta and Arnab Pal and Sudipta Ghosh and Debashish Kundu},
  journal={International Journal of Computer Applications},
Behaviors, actions, poses, facial expressions and speech; these are considered as channels that convey human emotions. Extensive research has being carried out to explore the relationships between these channels and emotions. This paper proposes a prototype system which automatically recognizes the emotion represented on a face. Thus a neural network based solution combined with image processing is used in classifying the universal emotions: Happiness, Sadness, Anger, Disgust, Surprise and Fear… 

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    2018 2nd International Conference on Inventive Systems and Control (ICISC)
  • 2018
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    2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)
  • 2021
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Results reveal that the system based on facial expression gave better performance than the systembased on just acoustic information for the emotions considered, and that when these two modalities are fused, the performance and the robustness of the emotion recognition system improve measurably.


An algorithm that utilizes multi-stage integral projection to extract facial features and a statistical approach to process the optical flow data to obtain the overall value for the respective feature region in the face are proposed.


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EMPATH: A Neural Network that Categorizes Facial Expressions

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  • Computer Science
  • 2013
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