|Table of Contents|

Face detection algorithm based on cascaded convolutional neural network(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2018年01期
Page:
40-
Research Field:
Publishing date:

Info

Title:
Face detection algorithm based on cascaded convolutional neural network
Author(s):
Sun KangLi QianmuLi Deqiang
School of Computer Science and Engineering,Nanjing University of Science and Technology,Nanjing 210094,China
Keywords:
face detection cascade structure neural network fully convolutional networks unconstrained condition
PACS:
TP391
DOI:
10.14177/j.cnki.32-1397n.2018.42.01.006
Abstract:
To overcome the problem that most of the methods based on depth learning cannot get a balance between speed and accuracy when directly extracting the depth of abstract features. This paper proposes a face detection method based on cascade neural network by combining traditional cascade framework with from-shallow-to-deep convolutional neural network. Firstly,this paper selects candidate face regions by means of fusing the confidence maps of images with part and full faces based on full convolutional neural network. Secondly,this paper extracts robust features of face to validate the candidate regions. Simultaneously,this paper locates the face with combined regression to improve the detection accuracy. In the experiments,the proposed method achieves comparable or better accuracy and speed on FDDB,AFW benchmarks.

References:

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Last Update: 2018-02-28