Abstract
People were able to convey intentions and feelings through non-verbal languages such as gestures and facial expressions. However, recognizing facial expressions is a very difficult task. Numerous factors such as light, posture, and distortion can cause complications. The proposed system is a good method for facial emotion detection problems. The system, which considers the elements of the face, will help to predict emotions from an image. Then histogram of oriented gradient (HOG) is used to encode these facial elements as features. A linear support vector machine is then used to identify facial expressions. The final results of this experiment show the accuracy of our prediction.
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Anu, K.A., Ali Akbar, N. (2022). Recognition of Facial Expressions Based on Detection of Facial Components and HOG Characteristics. In: Reddy, A.N.R., Marla, D., Favorskaya, M.N., Satapathy, S.C. (eds) Intelligent Manufacturing and Energy Sustainability. Smart Innovation, Systems and Technologies, vol 265. Springer, Singapore. https://doi.org/10.1007/978-981-16-6482-3_8
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DOI: https://doi.org/10.1007/978-981-16-6482-3_8
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