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Automatic Fiducial Points Detection for Multi-facial Expressions via Invariant Features and Multi-layer Kernel Sliding Perceptron

Title
Automatic Fiducial Points Detection for Multi-facial Expressions via Invariant Features and Multi-layer Kernel Sliding Perceptron
Author
김기범
Keywords
Fiducial points detection; Facial expression recognition; Kernel sliding perceptron; Mask generation; Optimization algorithm
Issue Date
2022-08-22
Publisher
SPRINGER SINGAPORE PTE LTD
Citation
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
Abstract
In recent years, automatic facial expression recognition (FER) is a primary processing method of non-verbal communication and conveys their intention states among human-machine interaction. In this paper, we have proposed a novel FER system that wisely detects automatic fiducial points, generates robust multi-perspective views facial masks and recognizes expressions via kernel sliding perceptron. Initially, we detect multiple faces in a scene via saliency factor and detect 38 fiducial points by connecting maximum interest points in each face. These points are used for generating a face mask by measuring triangles formation and B-spline curve fitting. Then, we extract invariant features, such as fused HOG-LBP, advance 0 degrees-180 degrees intensity and fast marching features, and seek the best points' junction optimizer with an artificial bee colony algorithm. Finally, we propose a novel multi-layer kernel sliding perceptron method to classify six basic facial expressions. The proposed system outperforms the existing well-known statistical state-of-the-art FER methods in terms of recognition accuracy of 91.05% over Chicago Faces and 88.50% over Fam2a datasets, respectively. The proposed system has a possible broader impact and potential applications of FER for multimodal intelligent systems.
URI
https://information.hanyang.ac.kr/#/eds/detail?an=edssjs.C0508673&dbId=edssjshttps://repository.hanyang.ac.kr/handle/20.500.11754/189660
ISSN
1975-0102; 2093-7423
DOI
10.1007/s42835-022-01220-1
Appears in Collections:
COLLEGE OF COMPUTING[E](소프트웨어융합대학) > MEDIA, CULTURE, AND DESIGN TECHNOLOGY(ICT융합학부) > Articles
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