Two-level algorithm of facial expressions classification on complex background

K. A. Sannikov, A. A. Bashlikov, A. A. Druki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The relevance of this study is stipulated by the necessity of designing algorithms allowing to improve the efficiency of human face detection and emotions recognition on images with complex background. Purpose: Development of algorithms and software system allowing to improve the efficiency of human face detection and in addition facial expression classification on images with complex background, in the presence of foreign objects, changing illumination, noise and different distortions. Experimental investigations to be performed into the efficiency of implemented algorithms and comparison to their existing analogs. Findings: Face detection algorithm based on Viola Jones method-is proposed to face detection on images with complex background. The model of convolutional neural network (CNN) with original structure is proposed for facial expression classification. The description of testing and training parameters, as well as comparisons with existing analogues are presented.

Original languageEnglish
Title of host publication2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509010806
DOIs
Publication statusPublished - 31 Jul 2017
Event2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Astana, Kazakhstan
Duration: 29 Jun 201730 Jun 2017

Publication series

Name2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Proceedings

Conference

Conference2017 International Siberian Conference on Control and Communications, SIBCON 2017
CountryKazakhstan
CityAstana
Period29.6.1730.6.17

Keywords

  • artificial neural networks
  • face detection
  • facial expression classification
  • Image processing
  • Viola-Jones algorithm

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Control and Optimization
  • Electrical and Electronic Engineering
  • Mechanical Engineering

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