Abstract
In the past few years Emotion detection from images has become very popular due to its immense applications fields in day-to-day life. Various computer visions techniques are applied to detect facial emotions but it’s a very challenging task in real time scenario. Most of real-life images are taken in the poor illumination condition and it fails to achieve good recognition accuracy. LBP and LTP both the textural feature descriptor come into the picture to overcome such condition. Histogram of Oriented Gradient (HOG) detects the edges and corners from the images very efficiently. Textural feature descriptor captures the local pattern. HOG and textural feature descriptor capture different types of information of the image. In the proposed method textural image and HOG image fusion is performed to increase the accuracy for recognizing the facial expression from images. The performance of proposed method is validated on CK+ dataset.
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Mukhopadhyay, M., Dey, A., Ghosh, A., Shaw, R.N. (2023). Facial Emotion Recognition Based on Textural Pattern and Histogram of Oriented Gradient. In: Shaw, R.N., Paprzycki, M., Ghosh, A. (eds) Advanced Communication and Intelligent Systems. ICACIS 2022. Communications in Computer and Information Science, vol 1749. Springer, Cham. https://doi.org/10.1007/978-3-031-25088-0_9
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