000			04167nam a22005415i 4500
001			978-981-13-2387-4
003			DE-He213
005			20240423125247.0
007			cr nn 008mamaa
008			191113s2020 si | s |||| 0|eng d
020			_a9789811323874 _9978-981-13-2387-4
024	7		_a10.1007/978-981-13-2387-4 _2doi
050		4	_aTA1634
072		7	_aUYQV _2bicssc
072		7	_aCOM016000 _2bisacsh
072		7	_aUYQV _2thema
082	0	4	_a006.37 _223
100	1		_aLin, Liang. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aHuman Centric Visual Analysis with Deep Learning _h[electronic resource] / _cby Liang Lin, Dongyu Zhang, Ping Luo, Wangmeng Zuo.
250			_a1st ed. 2020.
264		1	_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2020.
300			_aXII, 156 p. 53 illus., 46 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aPart I Motivation & Overview -- Chapter 1: The Foundation and Advances of Deep Learning -- Chapter 2. Human Centric Visual Analysis: Tasks and Progress -- Part II Localizing Persons in Images -- Chapter 3: Face Localization and Enhancement -- Chapter 4: Pedestrian Detection with RPN and Boosted Forests -- Part III Parsing Person In Details -- Chapter 5: Self-supervised Structure-sensitive Learning for Human Parsing -- Chapter 6: Instance-level Human Parsing -- Chapter 7: Video Instance-level Human Parsing -- Part IV Identifying and Verifying Persons -- Chapter 8: Person Verification -- Chapter 9: Face Verification -- Part V Higher Level Tasks -- Chapter 10: Human Activity Understanding.
520			_aThis book introduces the applications of deep learning in various human centric visual analysis tasks, including classical ones like face detection and alignment and some newly rising tasks like fashion clothing parsing. Starting from an overview of current research in human centric visual analysis, the book then presents a tutorial of basic concepts and techniques of deep learning. In addition, the book systematically investigates the main human centric analysis tasks of different levels, ranging from detection and segmentation to parsing and higher-level understanding. At last, it presents the state-of-the-art solutions based on deep learning for every task, as well as providing sufficient references and extensive discussions. Specifically, this book addresses four important research topics, including 1) localizing persons in images, such as face and pedestrian detection; 2) parsing persons in details, such as human pose and clothing parsing, 3) identifying and verifyingpersons, such as face and human identification, and 4) high-level human centric tasks, such as person attributes and human activity understanding. This book can serve as reading material and reference text for academic professors / students or industrial engineers working in the field of vision surveillance, biometrics, and human-computer interaction, where human centric visual analysis are indispensable in analysing human identity, pose, attributes, and behaviours for further understanding.
650		0	_aComputer vision.
650		0	_aPattern recognition systems.
650		0	_aBiometric identification.
650	1	4	_aComputer Vision.
650	2	4	_aAutomated Pattern Recognition.
650	2	4	_aBiometrics.
700	1		_aZhang, Dongyu. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aLuo, Ping. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aZuo, Wangmeng. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9789811323867
776	0	8	_iPrinted edition: _z9789811323881
856	4	0	_uhttps://doi.org/10.1007/978-981-13-2387-4
912			_aZDB-2-SCS
912			_aZDB-2-SXCS
942			_cSPRINGER
999			_c175999 _d175999