Abstract
Human-like facial expression recognition is the ultimate goal of all automatic facial expression recognition system. Facial expression recognition is mostly achieved by comparing the test image of a person with his/her neutral image. In this paper, “mean distance parameter” (MDP) has been proposed, and is used to recognize the facial expression. In this proposed methodology, database is not required to train the system for expression recognition, but neutral images from the database have been used only once for calculating the mean distance parameter. After establishment of the mean distance parameter based on region of interest (ROI) height, action units (AUs) have been detected by comparing it with the test image’s fiducial point distance. Facial expression recognition has been performed based on these detected AUs in the test image, and recognition rate of 96.66% has been achieved for Cohn-Kanade database.
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Kesarwani, P., Choudhary, A.K., Misra, A.K. (2019). Mean Distance Parameter Based Facial Expression Recognition System. In: Minz, S., Karmakar, S., Kharb, L. (eds) Information, Communication and Computing Technology. ICICCT 2018. Communications in Computer and Information Science, vol 835. Springer, Singapore. https://doi.org/10.1007/978-981-13-5992-7_16
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DOI: https://doi.org/10.1007/978-981-13-5992-7_16
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