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<dc:title xml:lang="pl"><![CDATA[Facial expression recognition under difficult conditions: A comprehensive study on edge directional texture patterns]]></dc:title>
<dc:creator><![CDATA[Ahmed, Faisal]]></dc:creator>
<dc:creator><![CDATA[Kabir, Md. Hasanul]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[directional ternary pattern]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[compressed DTP]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[facial feature descriptor]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[texture encoding]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[support vector machines]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[In recent years, research in automated facial expression recognition has attained significant attention for its potential applicability in human-computer interaction, surveillance systems, animation, and consumer electronics. However, recognition in uncontrolled environments under the presence of illumination and pose variations, low-resolution video, occlusion, and random noise is still a challenging research problem.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[In this paper, we investigate recognition of facial expression in difficult conditions by means of an effective facial feature descriptor, namely the directional ternary pattern (DTP). Given a face image, the DTP operator describes the facial feature by quantizing the eight-directional edge response values, capturing essential texture properties, such as presence of edges, corners, points, lines, etc. We also present an enhancement of the basic DTP encoding method, namely the compressed DTP (cDTP) that can describe the local texture more effectively with fewer features.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[The recognition performances of the proposed DTP and cDTP descriptors are evaluated using the Cohn-Kanade (CK) and the Japanese female facial expression (JAFFE) database. In our experiments, we simulate difficult conditions using original database images with lighting variations, low-resolution images obtained by down-sampling the original, and images corrupted with Gaussian noise. In all cases, the proposed method outperforms some of the well-known face feature descriptors.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Puig, Vicenç - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Sauter, Dominique - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Aubrun, Christophe - ed.]]></dc:contributor>
<dc:contributor><![CDATA[Schulte, Horst - ed.]]></dc:contributor>
<dc:date><![CDATA[2018]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/85846/AMCS_2018_28_2_14.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/100838/edition/85846/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:85846]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 28, number 2 (2018)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=papers&issue=108]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:100838]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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