A Fast Facial Landmarks Detection and Posture Classification Algorithm

2019 International Conference on Advanced Electronic Materials, Computers and Materials Engineering

无线电电子学;计算机科学;材料科学

Li, Shengyong^1 ; Zhang, Zhihua^1

Nantong Shipping College, Nantong,Jiangsu province

226000, China^1

关键词: Convolutional neural network;    Face images;    Facial landmark;    Network-based;    Posture classification;    Recall rate;    Relative positions;    Running time;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/563/5/052011/pdf
DOI  :  10.1088/1757-899X/563/5/052011

来源: IOP

【 摘 要 】

In the field of face recognition research, the efficiency of facial landmarks detection and posture classification algorithm is a serious problem. This paper proposes a lightweight network based on convolutional neural network to quickly detect the facial landmarks of human faces. Based on this, the posture is predicted using the relative position of the obtained feature points. The model was tested by the face images captured in various scenes in real life. The accuracy and recall rate of the proposed algorithm were 96.3% and 98.2%, respectively. The test time for a single picture is 0.9ms. The proposed algorithm has less running time and its accuracy and recall rate are similar or even better than other models.