Indonesian Journal of Electrical Engineering and Computer Science
Vol 16, No 2: November 2019

An optimization of facial feature point detection program by using several types of convolutional neural network

Shyota Shindo (Toyo University)
Takaaki Goto (Ryutsu Keizai University)
Tadaaki Kirishima (Toyo University)
Kensei Tsuchida (Toyo University)



Article Info

Publish Date
01 Nov 2019

Abstract

Detection of facial feature points is an important technique used for biometric authentication and facial expression estimation. A facial feature point is a local point indicating both ends of the eye, holes of the nose, and end points of the mouth in the face image. Many researches on face feature point detection have been done so far, but the accuracy of facial organ point detection is improving by the approach usingConvolutional Neural Network (CNN). However, CNN not only takes time to learn but also the neural network becomes a complicated model, so it is necessary to improve learning time and detection accuracy. In this research, the improvement of the detection accuracy of the learning speed is improved by increasing the convolution layer.

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