Two-level algorithm of facial expressions classification on complex background; Control and Communications (SIBCON-2017)
| Parent link: | Control and Communications (SIBCON-2017).— 2017.— [17082632] |
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| Autor Principal: | |
| Autor Corporativo: | |
| Outros autores: | , |
| Summary: | Title screen 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. Режим доступа: по договору с организацией-держателем ресурса |
| Idioma: | inglés |
| Publicado: |
2017
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| Subjects: | |
| Acceso en liña: | https://doi.org/10.1109/SIBCON.2017.7998594 |
| Formato: | Electrónico Capítulo de libro |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=655814 |
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| 200 | 1 | |a Two-level algorithm of facial expressions classification on complex background |f K. A. Sannikov, A. A. Bashlykov, A. A. Druki | |
| 203 | |a Text |c electronic | ||
| 300 | |a Title screen | ||
| 320 | |a [References: 15 tit.] | ||
| 330 | |a 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. | ||
| 333 | |a Режим доступа: по договору с организацией-держателем ресурса | ||
| 463 | 1 | |t Control and Communications (SIBCON-2017) |o proceedings of the XIII International Siberian Conference, June 29–30, 2017, Astana, Kazakhstan |v [17082632] |d 2017 | |
| 610 | 1 | |a электронный ресурс | |
| 610 | 1 | |a труды учёных ТПУ | |
| 610 | 1 | |a image processing | |
| 610 | 1 | |a artificial neural networks | |
| 610 | 1 | |a Viola-Jones algorithm | |
| 610 | 1 | |a face detection | |
| 610 | 1 | |a facial expression classification | |
| 610 | 1 | |a изображения | |
| 610 | 1 | |a обработка | |
| 610 | 1 | |a искусственные нейронные сети | |
| 610 | 1 | |a алгоритм Виолы-Джонса | |
| 610 | 1 | |a лица | |
| 610 | 1 | |a обнаружение | |
| 610 | 1 | |a выражения | |
| 610 | 1 | |a классификации | |
| 700 | 1 | |a Sannikov |b K. A. |g Konstantin Alekseevich | |
| 701 | 1 | |a Bashlykov |b A. A. |g Artyom Andreevich | |
| 701 | 1 | |a Druki |b A. A. |c specialist in the field of informatics and computer technology |c assistant of Tomsk Polytechnic University, engineer |f 1985- |g Aleksey Alekseevich |3 (RuTPU)RU\TPU\pers\34610 |9 17972 | |
| 712 | 0 | 2 | |a Томский политехнический университет |b Институт кибернетики, ИК |c 2010-2017 |9 27025 |
| 801 | 2 | |a RU |b 63413507 |c 20171005 |g RCR | |
| 856 | 4 | |u https://doi.org/10.1109/SIBCON.2017.7998594 | |
| 942 | |c CF | ||