A fusion of CNN And SIFT For multicultural facial expression recognition

作     者：Qadir, Inam Iqbal, Muhammad Amjad Ashraf, Samman Akram, Sheeraz 

作者机构：Department of Computer Science University of Central Punjab Lahore Pakistan Faculty of Computer Science and Information Technology The Superior University Lahore Pakistan  Lahore Pakistan 

出 版 物：《Multimedia Tools and Applications》 (Multimedia Tools Appl)

年 卷 期：2025年

页      面：1-19页

核心收录：

学科分类：0817[工学-化学工程与技术] 08[工学] 0703[理学-化学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Grafting (chemical) 

摘      要：The most generic and understandable way of communication is by observing facial expressions;Facial Expression Recognition(FER) performance was affected by the differences in ethnicity, culture, and geography. This research proposes a feature grafting-based novel technique to recognize multicultural facial expressions. The Viola-Jones algorithm detects the facial region of an image that is most concentrated. Feature Grafting is used to combine high-level and low-level features. A multicultural facial expression database was created using still images of male and female subjects obtained from three datasets: TFEID, Radboud, and JAFFE. The model is designed and tested using this dataset and the proposed technique. The obtained accuracy using the proposed technique was 94.34% which is better than the state-of-the-art method. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.