Face Detection Algorithm in Classroom Scene Based on Deep Learning

Yi Zhang, Chongwen Wang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

With informatisation progresses in education, the application of artificial intelligence technology in education is increasing day by day. Although some breakthroughs have been made, the application in specific scenes (such as classroom scenes) faces many difficulties, such as small target detection, severe occlusion, etc. We propose a target detection algorithm based on video data for the classroom scene, which combines the optical flow information to improve the accuracy and alleviate the impact of occlusion. We also put forward the counting method suitable for classroom scenes, which can be used as the evaluation standard of attendance rate, head-up rate, and other indicators in classroom quality evaluation.

Original languageEnglish
Title of host publicationAdvances in Computer Graphics - 39th Computer Graphics International Conference, CGI 2022, Proceedings
EditorsNadia Magnenat-Thalmann, Jian Zhang, Jinman Kim, George Papagiannakis, Bin Sheng, Daniel Thalmann, Marina Gavrilova
PublisherSpringer Science and Business Media Deutschland GmbH
Pages255-265
Number of pages11
ISBN (Print)9783031234729
DOIs
Publication statusPublished - 2022
Event39th Computer Graphics International Conference on Advances in Computer Graphics, CGI 2022 - Virtual, Online
Duration: 12 Sept 202216 Sept 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13443 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference39th Computer Graphics International Conference on Advances in Computer Graphics, CGI 2022
CityVirtual, Online
Period12/09/2216/09/22

Keywords

  • Face detection
  • Optical flow method
  • Target detection
  • Video analysis

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