國立虎尾科技大學 |

Human Centric Visual Analysis with Deep Learning

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Human Centric Visual Analysis with Deep Learning/ by Liang Lin, Dongyu Zhang, Ping Luo, Wangmeng Zuo.
Author:	Lin, Liang.
other author:	Zhang, Dongyu.
Description:	XII, 156 p. 53 illus., 46 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Optical data processing. -
Online resource:	https://doi.org/10.1007/978-981-13-2387-4
ISBN:	9789811323874

Human Centric Visual Analysis with Deep Learning
Lin, Liang.

Human Centric Visual Analysis with Deep Learning[electronic resource] /by Liang Lin, Dongyu Zhang, Ping Luo, Wangmeng Zuo. - 1st ed. 2020. - XII, 156 p. 53 illus., 46 illus. in color.online resource.

Part 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.

This 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 verifying persons, 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.

ISBN: 9789811323874

Standard No.: 10.1007/978-981-13-2387-4doiSubjects--Topical Terms:

639187
Optical data processing.

LC Class. No.: TA1630-1650

Dewey Class. No.: 006.6

Human Centric Visual Analysis with Deep Learning
LDR:03547nam a22004095i 4500 001 1025168
003 DE-He213
005 20200630005529.0
007 cr nn 008mamaa
008 210318s2020 si | s |||| 0|eng d
020 $a 9789811323874 $9 978-981-13-2387-4
024 7 $a 10.1007/978-981-13-2387-4 $2 doi
035 $a 978-981-13-2387-4
050 4 $a TA1630-1650
072 7 $a UYT $2 bicssc
072 7 $a COM012000 $2 bisacsh
072 7 $a UYT $2 thema
072 7 $a UYQV $2 thema
082 0 4 $a 006.6 $2 23
082 0 4 $a 006.37 $2 23
100 1 $a Lin, Liang. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1321372
245 1 0 $a Human Centric Visual Analysis with Deep Learning $h [electronic resource] / $c by Liang Lin, Dongyu Zhang, Ping Luo, Wangmeng Zuo.
250 $a 1st ed. 2020.
264 1 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2020.
300 $a XII, 156 p. 53 illus., 46 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a Part 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 $a This 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 verifying persons, 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 $a Optical data processing. $3 639187
650 0 $a Pattern recognition. $3 1253525
650 0 $a Biometrics (Biology). $3 1249740
650 1 4 $a Image Processing and Computer Vision. $3 670819
650 2 4 $a Pattern Recognition. $3 669796
650 2 4 $a Biometrics. $3 677095
700 1 $a Zhang, Dongyu. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1321373
700 1 $a Luo, Ping. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1321374
700 1 $a Zuo, Wangmeng. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1114538
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9789811323867
776 0 8 $i Printed edition: $z 9789811323881
856 4 0 $u https://doi.org/10.1007/978-981-13-2387-4
912 $a ZDB-2-SCS
912 $a ZDB-2-SXCS
950 $a Computer Science (SpringerNature-11645)
950 $a Computer Science (R0) (SpringerNature-43710)