{"id":1139,"date":"2021-01-15T21:54:26","date_gmt":"2021-01-15T19:54:26","guid":{"rendered":"http:\/\/journals.khnu.km.ua\/vestnik\/?p=1139"},"modified":"2021-03-23T11:40:33","modified_gmt":"2021-03-23T09:40:33","slug":"%d0%bc%d0%be%d0%b4%d0%b5%d0%bb%d1%8c-%d0%b4%d0%bb%d1%8f-%d1%80%d0%be%d0%b7%d0%bf%d1%96%d0%b7%d0%bd%d0%b0%d0%b2%d0%b0%d0%bd%d0%bd%d1%8f-%d0%bc%d1%96%d0%bc%d1%96%d1%87%d0%bd%d0%b8%d1%85-%d0%bf%d1%80","status":"publish","type":"post","link":"https:\/\/journals.khnu.km.ua\/vestnik\/?p=1139","title":{"rendered":"\u041c\u043e\u0434\u0435\u043b\u044c \u0434\u043b\u044f \u0440\u043e\u0437\u043f\u0456\u0437\u043d\u0430\u0432\u0430\u043d\u043d\u044f \u043c\u0456\u043c\u0456\u0447\u043d\u0438\u0445 \u043f\u0440\u043e\u044f\u0432\u0456\u0432"},"content":{"rendered":"

\u041c\u041e\u0414\u0415\u041b\u042c \u0414\u041b\u042f \u0420\u041e\u0417\u041f\u0406\u0417\u041d\u0410\u0412\u0410\u041d\u041d\u042f \u041c\u0406\u041c\u0406\u0427\u041d\u0418\u0425 \u041f\u0420\u041e\u042f\u0412\u0406\u0412 \u0415\u041c\u041e\u0426\u0406\u0419<\/p>\n

SIMPLIFIED MODEL FOR RECOGNITION FACIAL EMOTIONS<\/p>\n

<\/a> \u0421\u0442\u043e\u0440\u0456\u043d\u043a\u0438: 25-29. \u041d\u043e\u043c\u0435\u0440: \u21161, 2020 (281)<\/strong>
\n\u0410\u0432\u0442\u043e\u0440\u0438:<\/strong>
\n\u041e.\u0412. \u0411\u0410\u0420\u041c\u0410\u041a, \u041e.\u0414. \u041a\u0410\u041b\u0418\u0422\u0410, \u0415.\u0410. \u041c\u0410\u041d\u0417\u042e\u041a
\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
\nO. BARMAK, O. KALYTA, E. MANZIUK
\nKhmelnytsky National University
\nDOI:<\/strong> https:\/\/www.doi.org\/10.31891\/2307-5732-2020-281-1-25-29<\/a>
\n\u0420\u0435\u0446\u0435\u043d\u0437\u0456\u044f\/Peer review :<\/strong> 12. 01.2020 \u0440.
\n\u041d\u0430\u0434\u0440\u0443\u043a\u043e\u0432\u0430\u043d\u0430\/Printed :<\/strong> 14.02.2020 \u0440.<\/p>\n

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\u0434\u0430\u043b\u043e \u0437\u043c\u043e\u0433\u0443 \u0440\u0435\u0430\u043b\u0456\u0437\u0443\u0432\u0430\u0442\u0438 \u0440\u043e\u0437\u043f\u0456\u0437\u043d\u0430\u0432\u0430\u043d\u043d\u044f \u0437\u043c\u0456\u043d \u0435\u043c\u043e\u0446\u0456\u0439\u043d\u043e\u0433\u043e \u0441\u0442\u0430\u043d\u0443 \u043b\u044e\u0434\u0438\u043d\u0438 \u0437\u0430 \u043c\u0456\u043c\u0456\u0447\u043d\u0438\u043c\u0438 \u043f\u0440\u043e\u044f\u0432\u0430\u043c\u0438 \u043d\u0430 \u043e\u0431\u043b\u0438\u0447\u0447\u0456 \u0431\u0435\u0437 \u0432\u0438\u043a\u043e\u0440\u0438\u0441\u0442\u0430\u043d\u043d\u044f \u0441\u043f\u0435\u0446\u0456\u0430\u043b\u0456\u0437\u043e\u0432\u0430\u043d\u043e\u0433\u043e \u043e\u0431\u043b\u0430\u0434\u043d\u0430\u043d\u043d\u044f.<\/p>\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 \u043c\u0456\u043c\u0456\u0447\u043d\u0438\u0445 \u043f\u0440\u043e\u044f\u0432\u0456\u0432 \u0435\u043c\u043e\u0446\u0456\u0457, \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, \u0441\u043f\u0440\u043e\u0449\u0435\u043d\u0430 \u043c\u043e\u0434\u0435\u043b\u044c.<\/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 \u043c\u043e\u0432\u043e\u044e<\/strong><\/p>\n

There is a suggested approach for getting a simplified model to enable the realization of fast facial emotion recognition. The model realizes the hyperplane classification of mimic expressions of the main facial emotional states. The main advantage of this approach is small computational complexity, which will allow realizing the recognition of the changes in people\u2019s emotional state without any special equipment (for low-resolution or long-distance video cameras). The sphere of application is control over the drivers in the process of driving the vehicle, complex production operators, etc. As a result of the research and processing of the collected data, the main areas of the face were identified, in which changes in facial expressions directly affect the reflection of emotional states. These are areas with eyebrows, eyes, and lips. The final stage of the study was the definition of the variety of qualitative characteristics of the displacements of marks or groups of marks. To determine the forms of grouping states as a reflection of a set of features, we apply the approach proposed in the paper [9]. The approach allows the use of data visualization techniques to visually display characteristic forms of data grouping. These grouped data determine the classes of emotional displays. An important aspect is the ability to set the boundaries of class division, in our case, emotional states. The location of borders can be adjusted depending on the quality and quantity of data. This form of adaptation allows a more flexible application of the technology of recognition of mimic expressions of emotions and adaptation to the data body. Although mimic displays due to physiological particularities are typical displays of emotions,\u00a0 the boundaries of data separation need to be adjusted for accurate distinguishment of classes of emotions. This allows the use of hyperplane classification. The validity of the proposed model is suggested to test on the synthesized data. This is possible because the real input will belong to the same intervals as artificially created. The main advantage of the proposed approach is the small computational complexity that will allow the recognition of changes in the human emotional state by facial expressions without the use of specialized equipment (for low-resolution or long-distance video cameras).<\/p>\n

Keywords:<\/strong> facial emotion recognition, hyperlane classification, simplified model.<\/p>\n

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

    \n
  1. BARMAK, O. V., KALYTA O.D., HASHCHUK T.O. & SKRYPNYK, T. K. (2018) Information technology for determining the criteria of facial areas that reproduce emotional facial expressions \/\/ Herald of Khmelnytskyi national university. Technical Sciences, Issue 6, 2018 (2). p. 130-134.<\/li>\n
  2. INTEL\u00ae REALSENSE™ Depth Camera D435. [Online] Available from: https:\/\/www.intelrealsense.com\/depth-camera-d435\/ [Accessed: 15 January 2020].<\/li>\n
  3. KRAK I., BARMAK O., MANZIUK E., KULIAS A. (2020) Data Classification Based on the Features Reduction and Piecewise Linear Separation. In: Vasant P., Zelinka I., Weber GW. (eds) Intelligent Computing and Optimization. ICO 2019. Advances in Intelligent Systems and Computing, vol 1072. Springer, Cham.<\/li>\n
  4. COX T.F., COX M.A.A.: Multidimensional scaling, 2nd edn. Chapman and Hall \/ CRC, Boca Raton, 2001.<\/li>\n
  5. VAN DER MAATEN, L.J.P., POSTMA, E.O., VAN DEN HERIK, H.J.: Dimensionality reduction: a comparative review. Technical report TiCC-TR 2009-005. Tilburg University, 2009.<\/li>\n<\/ol>\n

     <\/p>\n","protected":false},"excerpt":{"rendered":"

    \u041c\u041e\u0414\u0415\u041b\u042c \u0414\u041b\u042f \u0420\u041e\u0417\u041f\u0406\u0417\u041d\u0410\u0412\u0410\u041d\u041d\u042f \u041c\u0406\u041c\u0406\u0427\u041d\u0418\u0425 \u041f\u0420\u041e\u042f\u0412\u0406\u0412 \u0415\u041c\u041e\u0426\u0406\u0419 SIMPLIFIED MODEL FOR RECOGNITION FACIAL EMOTIONS \u0421\u0442\u043e\u0440\u0456\u043d\u043a\u0438: 25-29. \u041d\u043e\u043c\u0435\u0440: \u21161, 2020 (281) \u0410\u0432\u0442\u043e\u0440\u0438: \u041e.\u0412. \u0411\u0410\u0420\u041c\u0410\u041a, \u041e.\u0414. \u041a\u0410\u041b\u0418\u0422\u0410, \u0415.\u0410. \u041c\u0410\u041d\u0417\u042e\u041a \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 O. BARMAK, O. KALYTA, E. MANZIUK Khmelnytsky National University DOI: https:\/\/www.doi.org\/10.31891\/2307-5732-2020-281-1-25-29 \u0420\u0435\u0446\u0435\u043d\u0437\u0456\u044f\/Peer review : 12. 01.2020 \u0440. \u041d\u0430\u0434\u0440\u0443\u043a\u043e\u0432\u0430\u043d\u0430\/Printed : 14.02.2020 \u0440. \u0410\u043d\u043e\u0442\u0430\u0446\u0456\u044f \u043c\u043e\u0432\u043e\u044e \u043e\u0440\u0438\u0433\u0456\u043d\u0430\u043b\u0443 \u0412 \u0441\u0442\u0430\u0442\u0442\u0456 \u0437\u0430\u043f\u0440\u043e\u043f\u043e\u043d\u043e\u0432\u0430\u043d\u043e […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[13],"tags":[],"_links":{"self":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/1139"}],"collection":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1139"}],"version-history":[{"count":3,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/1139\/revisions"}],"predecessor-version":[{"id":5072,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=\/wp\/v2\/posts\/1139\/revisions\/5072"}],"wp:attachment":[{"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1139"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1139"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/journals.khnu.km.ua\/vestnik\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1139"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}