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001441093 001__ 1441093
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001441093 0247_ $$a10.1007/978-981-16-6242-3$$2doi
001441093 035__ $$aSP(OCoLC)1286667282
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001441093 049__ $$aISEA
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001441093 08204 $$a006.3/7$$223
001441093 1001_ $$aXing, Weiwei,$$eauthor$$1https://orcid.org/0000-0002-6378-926X
001441093 24510 $$aVisual object tracking from correlation filter to deep learning /$$cWeiwei Xing, Weibin Liu, Jun Wang, Shunli Zhang, Lihui Wang, Yuxiang Yang, Bowen Song.
001441093 260__ $$aSingapore :$$bSpringer,$$c2021.
001441093 300__ $$a1 online resource (xiv, 193 pages) :$$billustrations.
001441093 336__ $$atext$$btxt$$2rdacontent
001441093 337__ $$acomputer$$bc$$2rdamedia
001441093 338__ $$aonline resource$$bcr$$2rdacarrier
001441093 347__ $$atext file
001441093 347__ $$bPDF
001441093 504__ $$aIncludes bibliographical references.
001441093 5050_ $$aIntroduction -- Algorithm foundations -- Correlation filter based visual object tracking -- Correlation filter with deep feature for visual object tracking -- Deep learning based visual object tracking -- Summary and future work.
001441093 506__ $$aAccess limited to authorized users.
001441093 520__ $$aThe book focuses on visual object tracking systems and approaches based on correlation filter and deep learning. Both foundations and implementations have been addressed. The algorithm, system design and performance evaluation have been explored for three kinds of tracking methods including correlation filter based methods, correlation filter with deep feature based methods, and deep learning based methods. Firstly, context aware and multi-scale strategy are presented in correlation filter based trackers; then, long-short term correlation filter, context aware correlation filter and auxiliary relocation in SiamFC framework are proposed for combining correlation filter and deep learning in visual object tracking; finally, improvements in deep learning based trackers including Siamese network, GAN and reinforcement learning are designed. The goal of this book is to bring, in a timely fashion, the latest advances and developments in visual object tracking, especially correlation filter and deep learning based methods, which is particularly suited for readers who are interested in the research and technology innovation in visual object tracking and related fields.
001441093 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 6, 2021).
001441093 650_0 $$aComputer vision.
001441093 650_0 $$aMachine learning.
001441093 650_6 $$aVision par ordinateur.
001441093 650_6 $$aApprentissage automatique.
001441093 655_0 $$aElectronic books.
001441093 7001_ $$aLiu, Weibin,$$eauthor$$1https://orcid.org/0000-0001-6246-0051
001441093 7001_ $$aWang, Jun,$$eauthor$$0(orcid)0000-0002-5901-9019$$1https://orcid.org/0000-0002-5901-9019
001441093 7001_ $$aZhang, Shunli,$$eauthor$$0(orcid)0000-0002-8186-8949$$1https://orcid.org/0000-0002-8186-8949
001441093 7001_ $$aWang, Lihui,$$eauthor.
001441093 7001_ $$aYang, Yuxiang,$$eauthor$$0(orcid)0000-0002-4750-7293$$1https://orcid.org/0000-0002-4750-7293
001441093 7001_ $$aSong, Bowen,$$eauthor.
001441093 77608 $$iPrint version:$$aXing, Weiwei.$$tVisual object tracking from correlation filter to deep learning.$$dSingapore : Springer, 2021$$z981166241X$$z9789811662416$$w(OCoLC)1264138162
001441093 852__ $$bebk
001441093 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-16-6242-3$$zOnline Access$$91397441.1
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001441093 980__ $$aBIB
001441093 980__ $$aEBOOK
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