Convolution neural network based face detection method and apparatus

A technology of convolutional neural network and face detection, which is applied in the field of face detection based on convolutional neural network, to achieve the effect of improving detection speed, avoiding time consumption, and powerful feature extraction ability

Active Publication Date: 2015-10-21
INST OF AUTOMATION CHINESE ACAD OF SCI
View PDF5 Cites 50 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method avoids the time consumption caused by the sliding window, and is conduci

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Convolution neural network based face detection method and apparatus
  • Convolution neural network based face detection method and apparatus
  • Convolution neural network based face detection method and apparatus

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0045]In order to describe the specific implementation method of the present invention in detail, the method of the present invention will be further described by taking a face detection database as an example. The database contains 3500 photos, including different scenes, such as day, night, indoor, outdoor, etc. When using the present invention to carry out face detection, proceed according to the following steps:

[0046] Step S1, all the photos in the database are scaled into grayscale images of the same size, and the label information of the pictures is divided into two categories according to whether each pixel of the picture belongs to a face, such as figure 2 shown.

[0047] Step S2, establishing a convolutional neural network with 5 convolutional layers and 3 fully connected layers, wherein the last fully connected layer has the same dimension as the input image, and all weights of the network are randomly initialized. The activation functions of the convolutional ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a convolution neural network based face detection method and apparatus. The method comprises the steps of: zooming all pictures in a training set into grayscale images of a predetermined size, and assigning label information to each pixel point of each picture, wherein the label information is used to show whether the pixel point that corresponds to the information is a face; establishing a convolution neural network, wherein layers of the convolution neural network are sequentially an input layer, a plurality of convolution layers, a plurality of full connectivity layers and an output layer; training the convolution neural network by using a gradient descent method and a back propagation algorithm; inputting a photograph to be detected into the well trained convolution neural network, so as to obtain an output characteristic value of a final layer; comparing the output characteristic value of a final layer to a predetermined threshold, so as to determine whether each pixel point of the photograph is a face region; and using a method of minimum closure, and detecting a face position according to pixel points that are determined as the face region.

Description

technical field [0001] The invention relates to the technical fields of pattern recognition and computer vision, in particular to a face detection method and device based on a convolutional neural network. Background technique [0002] Face detection is a very important problem in computer vision. With the growth of application requirements such as face recognition, age estimation, gender estimation and expression recognition, face detection, as the first step to complete these tasks, has gained more and more attention. The more people pay attention. Some traditional methods use sliding windows to detect faces, then judge each obtained window, and finally detect the position of the face. However, these methods use sliding window technology, which will take a lot of time in this link, and are not particularly suitable for some applications with high real-time requirements. Contents of the invention [0003] In order to solve the problems in the prior art, the object of th...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00
CPCG06V40/161
Inventor 王亮黄永祯张凯皓
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products