Muhammad Kashif1, Ayyaz Hussain2, Asim Munir1, Abdul Basit Siddiqui3, Aaqif Afzaal Abbasi4, Muhammad Aakif5, Arif Jamal Malik4, Fayez Eid Alazemi6, Oh-Young Song7,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2123-2139, 2021, DOI:10.32604/cmc.2021.014782
Abstract Expression detection plays a vital role to determine the patient’s condition in healthcare systems. It helps the monitoring teams to respond swiftly in case of emergency. Due to the lack of suitable methods, results are often compromised in an unconstrained environment because of pose, scale, occlusion and illumination variations in the image of the face of the patient. A novel patch-based multiple local binary patterns (LBP) feature extraction technique is proposed for analyzing human behavior using facial expression recognition. It consists of three-patch [TPLBP] and four-patch LBPs [FPLBP] based feature engineering respectively. Image representation is encoded from local patch statistics… More >
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