Efficient Face Detection Using Neural Networks

被引:1
作者
Sinha, Amit [1 ]
机构
[1] BIT Mesra, EEE Dept, Ranchi 835215, Jharkhand, India
来源
ADVANCES IN COMPUTATIONAL INTELLIGENCE | 2017年 / 509卷
关键词
Neural networks; Frontal face detection; Gradient descent; Scale invariance; Real time detection; Local feature detection;
D O I
10.1007/978-981-10-2525-9_27
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
There is a growing need for automated face recognition systems for various purpose, mainly security within organizations. The problem of face recognition consists of mainly 2 important steps. The first step is obtaining the region of the face from a raw image (face detection) and this is followed by a face recognition step to identify the individual. This paper gives an overview of the method used to detect the location of frontal faces in a small amount of time. The method involves creating a data set from a face database which has the localized parts of face images along with corresponding scores of the sectors of the face that are being detected. Based on the scores obtained further processing is done in the likely face area to determine whether a frontal face is present in the given region. This detection can be done in a small amount of time because the neural network can identify parts of a face from a kernel and not too many kernel operations are required to successfully identify the face.
引用
收藏
页码:279 / 285
页数:7
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