informИнформатикаInformatics1816-03012617-6963UIIP NASBinform-173Research ArticleОБРАБОТКА ИЗОБРАЖЕНИЙ И РАСПОЗНАВАНИЕ ОБРАЗОВРАСПОЗНАВАНИЕ ЭМОЦИЙ ПО ИЗОБРАЖЕНИЮ ЛИЦА С ИСПОЛЬЗОВАНИЕМ ТЕКСТУРНОГО АНАЛИЗАEMOTION RECOGNITION USING TEXTURE ANALYSISЖабинскийА. В.ZhabinskiA. V.andrei.zhabinski@gmail.comБелорусский государственный университет информатики и радиоэлектроникиBelarus201407102016048590Copyright © Жабинский А.В., 20162016Жабинский А.В.Zhabinski A.V.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://inf.grid.by/jour/article/view/173

Рассматривается роль текстуры (интенсивности пикселов) в задаче распознавания эмоций по изображению человеческого лица. Проводится сравнение текстуры и ключевых точек, а также предлагается комбинированный метод распознавания, объединяющий оба набора признаков.

In the paper the role of texture (pixel values) in a task of emotion recognition in the image of a face is explored. Texture-based method is compared to classic methods based on coordinates of key point. In addition, a new combined method is presented that unites both sets of features.

ReferencesMehrabian, A. Communication without words / A. Mahrabian // Psychology Today. – 1968. – Vol. 2, no. 4. – P. 53–56.Mehrabian, A. Communication without words / A. Mahrabian // Psychology Today. – 1968. – Vol. 2, no. 4. – P. 53–56.Tian, Y. Facial expression recognition / Y. Tian, T. Kanade, J. F. Cohn // Handbook of face recognition. – London : Springer, 2011. – P. 487–519.Tian, Y. Facial expression recognition / Y. Tian, T. Kanade, J. F. Cohn // Handbook of face recognition. – London : Springer, 2011. – P. 487–519.Littlewort, G. Dynamics of facial expression extracted automatically from video / G. Little-wort, M.S. Bartlett, I. Fasel // Image and Computer Vision. – 2004. – Vol. 24, no. 6. – P. 615–625.Littlewort, G. Dynamics of facial expression extracted automatically from video / G. Little-wort, M.S. Bartlett, I. Fasel // Image and Computer Vision. – 2004. – Vol. 24, no. 6. – P. 615–625.Shana, С. Facial expression recognition based on Local Binary Patterns: A comprehensive study / C. Shana, S. Gong, P.W McOwanb // Image and Vision Computing. – 2009. – Vol. 27, no. 6. – P. 803–816.Shana, С. Facial expression recognition based on Local Binary Patterns: A comprehensive study / C. Shana, S. Gong, P.W McOwanb // Image and Vision Computing. – 2009. – Vol. 27, no. 6. – P. 803–816.Senechal, T. Impact of action unit detection in automatic emotion recognition / T. Senechal, K. Bailly, L. Prevost // Pattern Analysis and Applications. – 2014. – Vol. 17, no. 1. – P. 51–67.Senechal, T. Impact of action unit detection in automatic emotion recognition / T. Senechal, K. Bailly, L. Prevost // Pattern Analysis and Applications. – 2014. – Vol. 17, no. 1. – P. 51–67.Cootes, T.F. Active appearance models / T.F. Cootes, G.J. Edwards, C.J. Taylor // Lecture Notes in Computer Science. – 1998. – Vol. 1407. – P. 484–498.Cootes, T.F. Active appearance models / T.F. Cootes, G.J. Edwards, C.J. Taylor // Lecture Notes in Computer Science. – 1998. – Vol. 1407. – P. 484–498.Matthews, I. Active appearance models revisited / I. Matthews, S. Baker. // Intern. J. of Computer Vision. – 2004. – Vol. 60, no. 2. – P. 135–164.Matthews, I. Active appearance models revisited / I. Matthews, S. Baker. // Intern. J. of Computer Vision. – 2004. – Vol. 60, no. 2. – P. 135–164.Ratliff, M.S. Active appearance models for affect recognition using facial expressions: thesis by MD in CS / M.S. Ratliff. – Wilmington, 2010. – Vol. 4. – 89 p.Ratliff, M.S. Active appearance models for affect recognition using facial expressions: thesis by MD in CS / M.S. Ratliff. – Wilmington, 2010. – Vol. 4. – 89 p.DeepFace: closing the gap to human-level performance in face verification / Y. Taigman [et al.] // Conference in Computer Vision and Pattern Recognition. – Columbus, OH, USA, 2014. – P. 1701–1708.DeepFace: closing the gap to human-level performance in face verification / Y. Taigman [et al.] // Conference in Computer Vision and Pattern Recognition. – Columbus, OH, USA, 2014. – P. 1701–1708.Kanade, T. Comprehensive database for facial expression analysis / T. Kanade, J.F. Cohn, Y. Tian // Proc. of the Fourth IEEE Intern. Conf. on Automatic Face and Gesture Recognition. – Gre-noble, France, 2000. – P. 46.Kanade, T. Comprehensive database for facial expression analysis / T. Kanade, J.F. Cohn, Y. Tian // Proc. of the Fourth IEEE Intern. Conf. on Automatic Face and Gesture Recognition. – Gre-noble, France, 2000. – P. 46.Lucey, P. The Extended Cohn-Kanade Dataset (CK+): A complete expression dataset for action unit and emotion-specified expression / P. Lucey, J.F. Cohn., T. Kanade // Proc. of the Third Intern. Workshop on CVPR for Human Communicative Behavior Analysis. – San Francisco, CA, USA, 2010. – P. 94–101.Lucey, P. The Extended Cohn-Kanade Dataset (CK+): A complete expression dataset for action unit and emotion-specified expression / P. Lucey, J.F. Cohn., T. Kanade // Proc. of the Third Intern. Workshop on CVPR for Human Communicative Behavior Analysis. – San Francisco, CA, USA, 2010. – P. 94–101.Библиотека AAMToolbox [Электронный ресурс] – Режим доступа : https://github.com/phoenix367/AAMToolbox. – Дата доступа : 01.06.2014.Библиотека AAMToolbox [Электронный ресурс] – Режим доступа : https://github.com/phoenix367/AAMToolbox. – Дата доступа : 01.06.2014.

The authors declare that there are no conflicts of interest present.