{"id":12155,"date":"2022-04-20T10:20:17","date_gmt":"2022-04-20T07:20:17","guid":{"rendered":"http:\/\/journals.khnu.km.ua\/vestnik\/?p=12155"},"modified":"2022-04-20T13:35:04","modified_gmt":"2022-04-20T10:35:04","slug":"metod-geometrychnoyi-interpretacziyi-dilyanok-oblychchya-dlya-identyfikacziyi-zmin-emoczijnogo-stanu","status":"publish","type":"post","link":"https:\/\/journals.khnu.km.ua\/vestnik\/?p=12155","title":{"rendered":"\u041c\u0435\u0442\u043e\u0434 \u0433\u0435\u043e\u043c\u0435\u0442\u0440\u0438\u0447\u043d\u043e\u0457 \u0456\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0456\u0457 \u0434\u0456\u043b\u044f\u043d\u043e\u043a \u043e\u0431\u043b\u0438\u0447\u0447\u044f \u0434\u043b\u044f \u0456\u0434\u0435\u043d\u0442\u0438\u0444\u0456\u043a\u0430\u0446\u0456\u0457 \u0437\u043c\u0456\u043d \u0435\u043c\u043e\u0446\u0456\u0439\u043d\u043e\u0433\u043e \u0441\u0442\u0430\u043d\u0443"},"content":{"rendered":"

<\/p>\n

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METHOD OF GEOMETRIC INTERPRETATION OF FACIAL EXPRESSIONS FOR EMOTIONS RECOGNITION<\/p>\n

\u00a0<\/strong>\u0421\u0442\u043e\u0440\u0456\u043d\u043a\u0438: 68-71. \u041d\u043e\u043c\u0435\u0440: \u2116<\/strong>1<\/strong>, 202<\/strong>2<\/strong> (<\/strong>305<\/strong>)\u00a0 \"\"<\/a> <\/strong>
\n\u00a0<\/strong>\u0410\u0432\u0442\u043e\u0440\u0438:<\/strong>
\n\u041a\u0410\u041b\u0418\u0422\u0410 \u041e. \u0414.
\nhttps:\/\/orcid.org\/0000-0003-1868-8803<\/a>
\ne-mail: oleg.kalyta@gmail.com<\/a>
\n\u0425\u043c\u0435\u043b\u044c\u043d\u0438\u0446\u044c\u043a\u0438\u0439 \u043d\u0430\u0446\u0456\u043e\u043d\u0430\u043b\u044c\u043d\u0438\u0439 \u0443\u043d\u0456\u0432\u0435\u0440\u0441\u0438\u0442\u0435\u0442
\nOleg KALYTA
\nKhmelnytskyi National University
\nDOI:<\/strong> https:\/\/www.doi.org\/10.31891\/2307-5732-2022-305-1–68-71<\/a><\/p>\n

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\n\u041a\u043b\u044e\u0447\u043e\u0432\u0456 \u0441\u043b\u043e\u0432\u0430:<\/strong> \u0440\u043e\u0437\u043f\u0456\u0437\u043d\u0430\u0432\u0430\u043d\u043d\u044f \u0435\u043c\u043e\u0446\u0456\u0439, \u0432\u0438\u044f\u0432\u043b\u0435\u043d\u043d\u044f \u043e\u0431\u043b\u0438\u0447\u0447\u044f, \u043c\u0456\u043c\u0456\u0447\u043d\u0456 \u043f\u0440\u043e\u044f\u0432\u0438, \u043a\u0456\u043b\u044c\u043a\u0456\u0441\u043d\u0430 \u0456\u043d\u0442\u0435\u0440\u043f\u0440\u0435\u0442\u0430\u0446\u0456\u044f \u043e\u0431\u043b\u0438\u0447\u0447\u044f, \u0456\u043d\u0444\u043e\u0440\u043c\u0430\u0446\u0456\u0439\u043d\u0430 \u0431\u0435\u0437\u043f\u0435\u043a\u0430, \u0433\u0456\u043f\u0435\u0440\u043f\u043b\u043e\u0449\u0438\u043d\u043d\u0430 \u043a\u043b\u0430\u0441\u0438\u0444\u0456\u043a\u0430\u0446\u0456\u044f<\/p>\n

\u0420\u043e\u0437\u0448\u0438\u0440\u0435\u043d\u0430 \u0430\u043d\u043e\u0442\u0430\u0446\u0456\u044f \u0430\u043d\u0433\u043b\u0456\u0439\u0441\u044c\u043a\u043e\u044e \u00a0\u043c\u043e\u0432\u043e\u044e<\/strong><\/p>\n

Emotional expressions serve a crucial role in interpersonal communication between people while improving social life. In particular, information security systems for visual surveillance that aim to recognize human emotional facial states are highly relevant today. Facial expressions are among the most effective and straightforward means of nonverbal interaction in systems with a human-machine interface. Despite significant scientific and engineering advances in emotion recognition, there are still several challenges in improving the performance of real-time human-machine systems that might work more effectively. In this work, a method of facial geometric feature representation is proposed to improve the operation of security systems. The method is designed to automatically reflect the facial expressions of human emotions in the form of quantitative characteristics of geometric shapes. It uses software-generated landmarks for constructing specific geometric characteristics of the face, which serve as input for the method. Our method consists in forming seven geometric shapes based on predefined landmarks, with the subsequent quantitative expression of these shapes. It was established within the method that the movement of the landmarks when changing facial expressions directly changed the value of each geometric shape. The method outputs the quantitative features of seven shapes, later used to classify emotional facial states. Finally, our method was validated using hyperplane classification. The results of computational experiments confirmed the effectiveness of the proposed method for identifying changes in a person\u2019s emotional state by facial expressions. In addition, the use of simple mathematical calculations in our method has significantly reduced the computational complexity against analogs.
\nKeywords:<\/strong> Emotion recognition, face detection, facial extractions, geometric feature, face orientation, information security, hyperplane classification<\/p>\n

\u041b\u0456\u0442\u0435\u0440\u0430\u0442\u0443\u0440\u0430<\/strong><\/p>\n

    \n
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  2. Ekman\u00a0P. The facial action coding system: The manual \/ P.\u00a0Ekman, W.\u00a0V.\u00a0Friesen, J.\u00a0C.\u00a0Hager \/\/ UT Research Nexus eBook. \u2013 Salt Lake City, 2002. \u2013 527 p.<\/li>\n
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  5. Nasir\u00a0M. Fuzzy triangulation signature for detection of change in human emotion from face video image sequence\u00a0\/ M.\u00a0Nasir, P.\u00a0Dutta, A.\u00a0Nandi\u00a0\/\/ Multimedia Tools and Applications. \u2013 2021. \u2013 Vol.\u00a080. \u2013 P.\u00a031993\u201332022.<\/li>\n
  6. Barmak\u00a0O. Model of the facial emotions expressions based on grouping classes of feature vectors\u00a0\/ O.\u00a0Barmak, O.\u00a0Kalyta, Iu.\u00a0Krak, E.\u00a0Manziuk, V.\u00a0Kuznetsov\u00a0\/\/ Advances in Intelligent Systems and Computing. \u2013 Cham, 2020. \u2013 Vol. 1246. \u2013 P.\u00a065\u201376.<\/li>\n
  7. Van der Schalk\u00a0J. Moving faces, looking places: Validation of the Amsterdam dynamic facial expression set (ADFES) \/ J.\u00a0van der Schalk, S.\u00a0T.\u00a0Hawk, A.\u00a0H.\u00a0Fischer, B.\u00a0Doosje \/\/ Emotion. \u2013 2011. \u2013 Vol.\u00a011, No.\u00a04. \u2013 P.\u00a0907\u2013920.<\/li>\n
  8. Barmak\u00a0A.\u00a0V. Information technology of separating hyperplanes synthesis for linear classifiers \/ A.\u00a0V.\u00a0Barmak, Y.\u00a0V.\u00a0Krak, E.\u00a0A.\u00a0Manziuk, V.\u00a0S.\u00a0Kasianiuk \/\/ Journal of Automation and Information Sciences. \u2013 2019. \u2013 Vol.\u00a051, No.\u00a05. \u2013 P.\u00a054\u201364.<\/li>\n<\/ol>\n

    References<\/strong><\/p>\n

      \n
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    2. Ekman\u00a0P. The facial action coding system: The manual \/ P.\u00a0Ekman, W.\u00a0V.\u00a0Friesen, J.\u00a0C.\u00a0Hager \/\/ UT Research Nexus eBook. \u2013 Salt Lake City, 2002. \u2013 527 p.<\/li>\n
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    5. Nasir\u00a0M. Fuzzy triangulation signature for detection of change in human emotion from face video image sequence\u00a0\/ M.\u00a0Nasir, P.\u00a0Dutta, A.\u00a0Nandi\u00a0\/\/ Multimedia Tools and Applications. \u2013 2021. \u2013 Vol.\u00a080. \u2013 P.\u00a031993\u201332022.<\/li>\n
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