<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">inform</journal-id><journal-title-group><journal-title xml:lang="ru">Информатика</journal-title><trans-title-group xml:lang="en"><trans-title>Informatics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1816-0301</issn><issn pub-type="epub">2617-6963</issn><publisher><publisher-name>UIIP NASB</publisher-name></publisher></journal-meta><article-meta><article-id custom-type="elpub" pub-id-type="custom">inform-686</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ОБРАБОТКА СИГНАЛОВ, ИЗОБРАЖЕНИЙ, РЕЧИ, ТЕКСТА И РАСПОЗНАВАНИЕ ОБРАЗОВ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>SIGNAL, IMAGE, SPEECH, TEXT PROCESSING AND PATTERN RECOGNITION</subject></subj-group></article-categories><title-group><article-title>ОТСЛЕЖИВАНИЕ ДИНАМИЧЕСКИХ ОБЪЕКТОВ И ИХ РАСПОЗНАВАНИЕ С ПОМОЩЬЮ ГРАФОВЫХ АЛГОРИТМОВ</article-title><trans-title-group xml:lang="en"><trans-title></trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Залесский</surname><given-names>Б. А.</given-names></name></name-alternatives><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кравчонок</surname><given-names>А. И.</given-names></name></name-alternatives><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff xml:lang="ru" id="aff-1"><institution>Объединенный институт проблем информатики НАН Беларуси</institution><country>Belarus</country></aff><pub-date pub-type="collection"><year>2006</year></pub-date><pub-date pub-type="epub"><day>13</day><month>12</month><year>2018</year></pub-date><volume>0</volume><issue>2(10)</issue><fpage>17</fpage><lpage>26</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Залесский Б.А., Кравчонок А.И., 2018</copyright-statement><copyright-year>2018</copyright-year><copyright-holder xml:lang="ru">Залесский Б.А., Кравчонок А.И.</copyright-holder><copyright-holder xml:lang="en">Залесский Б.А., Кравчонок А.И.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://inf.grid.by/jour/article/view/686">https://inf.grid.by/jour/article/view/686</self-uri><abstract><p>Предлагаются методы и алгоритмы отслеживания и распознавания объектов на цветных видеопоследовательностях, снятых стационарной видеокамерой. Разработанные алгоритмы дают возможность отслеживать и распознавать динамические объекты в режиме реального времени. Использование цветных изображений позволяет повысить качество решения задачи. Выделение, сегментация и отслеживание объектов осуществляются с помощью кластерных представлений объектов.</p></abstract></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Lucas, B.D. An iterative image registration technique with an application to stereo vision / B.D. Lucas, T. Kanade // Proc. International Joint Conference on Artificial Intelligence. – Vancouver, Canada, 1981. – P. 674–679.</mixed-citation><mixed-citation xml:lang="en">Lucas, B.D. An iterative image registration technique with an application to stereo vision / B.D. Lucas, T. Kanade // Proc. International Joint Conference on Artificial Intelligence. – Vancouver, Canada, 1981. – P. 674–679.</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Shi, J. Good features to track / J. Shi, C. Tomasi // IEEE Conference on Compurer Vision and Pattern Recognition (CVPR94). – Seattle, 1994. – P. 593–600.</mixed-citation><mixed-citation xml:lang="en">Shi, J. Good features to track / J. Shi, C. Tomasi // IEEE Conference on Compurer Vision and Pattern Recognition (CVPR94). – Seattle, 1994. – P. 593–600.</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Matthies, L.H. Kalman filter-based algorithms for estimating depth from image sequences / L.H. Matthies, T. Kanade, R. Szeliski // Int. Journal of Computer Vision. – Vol. 3. – 1989. – P. 209–236.</mixed-citation><mixed-citation xml:lang="en">Matthies, L.H. Kalman filter-based algorithms for estimating depth from image sequences / L.H. Matthies, T. Kanade, R. Szeliski // Int. Journal of Computer Vision. – Vol. 3. – 1989. – P. 209–236.</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Isard, M. Condensation – conditional density propagation for visual tracking / M. Isard, A. Blake // Int. Journal of Computer Vision. – 1998. – № 29(1). – P. 5–28.</mixed-citation><mixed-citation xml:lang="en">Isard, M. Condensation – conditional density propagation for visual tracking / M. Isard, A. Blake // Int. Journal of Computer Vision. – 1998. – № 29(1). – P. 5–28.</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Isard, M. BraMBLe: A Bayesian Multiple-Blob Tracker / M. Isard, J. MacCormick // International Conference on Computer Vision. – Vancouver, Canada, 2001. – Vol. 2. – P. 34–41.</mixed-citation><mixed-citation xml:lang="en">Isard, M. BraMBLe: A Bayesian Multiple-Blob Tracker / M. Isard, J. MacCormick // International Conference on Computer Vision. – Vancouver, Canada, 2001. – Vol. 2. – P. 34–41.</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">A Tutorial on Particle Filters for On-line Non-linear/Non-Gaussian Bayesian Tracking / S. Arulampalam [et al.] // IEEE Transactions on signal processing. – V. 50. – № 2. – 2001. – P. 174–188.</mixed-citation><mixed-citation xml:lang="en">A Tutorial on Particle Filters for On-line Non-linear/Non-Gaussian Bayesian Tracking / S. Arulampalam [et al.] // IEEE Transactions on signal processing. – V. 50. – № 2. – 2001. – P. 174–188.</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Залесский, Б.А. Отслеживание и распознавание движущихся объектов на основе их кластерного представления / Б.А. Залесский, А.И. Кравчонок // Информатика. – № 2. – 2004. – C. 68–78.</mixed-citation><mixed-citation xml:lang="en">Залесский, Б.А. Отслеживание и распознавание движущихся объектов на основе их кластерного представления / Б.А. Залесский, А.И. Кравчонок // Информатика. – № 2. – 2004. – C. 68–78.</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Лекции по теории графов / В. А. Емеличев [и др.] – М.: Наука, 1990.</mixed-citation><mixed-citation xml:lang="en">Лекции по теории графов / В. А. Емеличев [и др.] – М.: Наука, 1990.</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
