Two-level algorithm of facial expressions classification on complex background

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

Результат исследований: Материалы для книги/типы отчетовМатериалы для конференции

2 Цитирования (Scopus)

Аннотация

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.

Язык оригиналаАнглийский
Название основной публикации2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Proceedings
ИздательInstitute of Electrical and Electronics Engineers Inc.
ISBN (электронное издание)9781509010806
DOI
СостояниеОпубликовано - 31 июл 2017
Событие2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Astana, Казахстан
Продолжительность: 29 июн 201730 июн 2017

Серия публикаций

Название2017 International Siberian Conference on Control and Communications, SIBCON 2017 - Proceedings

Конференция

Конференция2017 International Siberian Conference on Control and Communications, SIBCON 2017
СтранаКазахстан
ГородAstana
Период29.6.1730.6.17

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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