Отрывок: For comparison, we run 3 state-of-the-art algorithms with the same initial position of the target. The first tracking algorithm (SURF) [28] is based on matching of local features and descriptors. The second tracking algori...
Полная запись метаданных
Поле DC | Значение | Язык |
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dc.contributor.author | Ruchay, A.N. | - |
dc.contributor.author | Kober, V.I. | - |
dc.contributor.author | Chernoskulov, I.E. | - |
dc.date.accessioned | 2017-05-12 16:26:57 | - |
dc.date.available | 2017-05-12 16:26:57 | - |
dc.date.issued | 2017 | - |
dc.identifier | Dspace\SGAU\20170512\63730 | ru |
dc.identifier.citation | Ruchay A.N. Real-time tracking of multiple objects with locally adaptive correlation filters / A.N. Ruchay, V.I. Kober, I.E. Chernoskulov // Сборник трудов III международной конференции и молодежной школы «Информационные технологии и нанотехнологии» (ИТНТ-2017) - Самара: Новая техника, 2017. - С. 513-517. | ru |
dc.identifier.uri | http://repo.ssau.ru/handle/Informacionnye-tehnologii-i-nanotehnologii/Realtime-tracking-of-multiple-objects-with-locally-adaptive-correlation-filters-63730 | - |
dc.description.abstract | A tracking algorithm using locally adaptive correlation filtering is proposed. The algorithm is designed to track multiple objects withinvariancetopose,occlusion,clutter,andilluminationvariations. Thealgorithmemploysapredictionschemeandcomposite correlationfilters. Thefiltersaresynthesizedwiththehelpofaniterativealgorithm,whichoptimizesdiscriminationcapabilityfor each target. The filters are adapted online to targets changes using information of current and past scene frames. Results obtained with the proposed algorithm using real-life scenes, are presented and compared with those obtained with state-of-the-art tracking methods in terms of detection efficiency, tracking accuracy, and speed of processing. | ru |
dc.description.sponsorship | This work was supported by the Russian Science Foundation, grant no. 15-19-10010. | ru |
dc.language.iso | en_US | ru |
dc.publisher | Новая техника | ru |
dc.subject | tracking | ru |
dc.subject | locally adaptive filters | ru |
dc.subject | correlation filters | ru |
dc.subject | matching | ru |
dc.title | Real-time tracking of multiple objects with locally adaptive correlation filters | ru |
dc.type | Article | ru |
dc.textpart | For comparison, we run 3 state-of-the-art algorithms with the same initial position of the target. The first tracking algorithm (SURF) [28] is based on matching of local features and descriptors. The second tracking algori... | - |
Располагается в коллекциях: | Информационные технологии и нанотехнологии |
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paper 100_513-517.pdf | Основная статья | 317.65 kB | Adobe PDF | Просмотреть/Открыть |
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