Development of video-based emotion recognition using deep learning with Google Colab

[...]frames are to be extracted from the input video [4]. Face detection Emotions are featured mainly from the face. [...]it is crucial to detect the face to obtain facial features for further processing and recognition. [...]resizing is very important to shorten the processing time. [...]better res...

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Bibliographic Details
Published in:Telkomnika 2020-10, Vol.18 (5), p.2463-2471
Main Authors: Gunawan, Teddy Surya, Ashraf, Arselan, Riza, Bob Subhan, Haryanto, Edy Victor, Rosnelly, Rika, Kartiwi, Mira, Janin, Zuriati
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Architecture
Artificial intelligence
Deep learning
Emotions
Face recognition
Human-computer interaction
Image classification
Machine learning
Neural networks
Optimization
Researchers
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Summary:[...]frames are to be extracted from the input video [4]. Face detection Emotions are featured mainly from the face. [...]it is crucial to detect the face to obtain facial features for further processing and recognition. [...]resizing is very important to shorten the processing time. [...]better resizing techniques should be used to preserve image attributes after resizing [8]. The accuracy of the classification depends on whether the features are well representing the expression or not. [...]the optimization of the selected features will automatically improve classification accuracy [9].
ISSN:1693-6930
2302-9293
DOI:10.12928/telkomnika.v18i5.16717