Landmark-based Multi-Points Warping Approach to 3D Facial Expression Recognition in Human

被引：0

作者：

Agbolade, Olalekan ^{[1
]}

Nazri, Azree ^{[1
]}

Yaakob, Razali ^{[1
]}

Ghani, Abdul Azim ^{[2
]}

Cheah, Yoke Kqueen ^{[1
]}

机构：

[1] Univ Putra Malaysia, Fac Comp Sci & IT, Dept Comp Sci, Serdang, Selangor, Malaysia

[2] Univ Putra Malaysia, Fac Comp Sci & IT, Dept Software Engn, Serdang, Selangor, Malaysia

来源：

2019 1ST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND DATA SCIENCES (AIDAS2019) | 2019年

关键词：

Facial Expression Recognition; 3D faces; Multi-point warping; automatic facial landmark; PCA; LDA; FACE;

D O I：

10.1109/aidas47888.2019.8970972

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision. This is due to the current challenges facing facial data acquisition in 3D: such as lack of homology and complex mathematical analysis for facial point digitization. This study proposes facial expression recognition in human with the application of Multi-points Warping for 3D facial landmark. The results indicate that Fear expression has the lowest recognition accuracy while Surprise expression has the highest recognition accuracy. The classifier achieved a recognition accuracy of 99.58%.

引用

页码：180 / 185

页数：6

共 39 条

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