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008			211118s2021 si | s |||| 0|eng d
020			_a9789811662423
024	7		_a10.1007/978-981-16-6242-3 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTA1634 _b2021 EB
100	1		_aXing, Weiwei _9682205
245	1	0	_aVisual Object Tracking from Correlation Filter to Deep Learning _cby Weiwei Xing, Weibin Liu, Jun Wang, Shunli Zhang, Lihui Wang, Yuxiang Yang, Bowen Song
250			_aFirst edition 2021
264		1	_aSingapore _bSpringer International Publising _c2021
300			_a1 recurso en línea (XIV, 193 páginas) _b125 ilustraciones, 84 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aarchivo de texto _bPDF
490	0		_aComputer Science (SpringerNature-11645)
490	0		_aComputer Science (R0) (SpringerNature-43710)
505	0		_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.
520	3		_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.
988			_aSpringer_Computer_2021
650		7	_2embne _9159793 _aVisión por ordenador
700	1		_aLiu, Weibin _eautor _0(orcid)0000-0001-6246-0051 _1https://orcid.org/0000-0001-6246-0051 _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aWang, Jun _eautor _0(orcid)0000-0002-5901-9019 _1https://orcid.org/0000-0002-5901-9019 _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aZhang, Shunli _eautor _0(orcid)0000-0002-8186-8949 _1https://orcid.org/0000-0002-8186-8949 _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aWang, Lihui _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aYang, Yuxiang _eautor _0(orcid)0000-0002-4750-7293 _1https://orcid.org/0000-0002-4750-7293 _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aSong, Bowen _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-981-16-6242-3 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b02/2022 _dz _eh _zSI