國立高雄大學圖資館 |

Language: English

Back

Sparse representation, modeling and ...

Cheng, Hong.

Sparse representation, modeling and learning in visual recognitiontheory, algorithms and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Sparse representation, modeling and learning in visual recognitionby Hong Cheng.
Reminder of title:	theory, algorithms and applications /
Author:	Cheng, Hong.
Published:	London :Springer London :2015.
Description:	xiv, 257 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Computer vision.
Online resource:	http://dx.doi.org/10.1007/978-1-4471-6714-3
ISBN:	9781447167143 (electronic bk.)

Sparse representation, modeling and learning in visual recognitiontheory, algorithms and applications /
Cheng, Hong.

Sparse representation, modeling and learning in visual recognitiontheory, algorithms and applications /[electronic resource] :by Hong Cheng. - London :Springer London :2015. - xiv, 257 p. :ill., digital ;24 cm. - Advances in computer vision and pattern recognition,2191-6586. - Advances in computer vision and pattern recognition..

Part I: Introduction and Fundamentals -- Introduction -- The Fundamentals of Compressed Sensing -- Part II: Sparse Representation, Modeling and Learning -- Sparse Recovery Approaches -- Robust Sparse Representation, Modeling and Learning -- Efficient Sparse Representation and Modeling -- Part III: Visual Recognition Applications -- Feature Representation and Learning -- Sparsity Induced Similarity -- Sparse Representation and Learning Based Classifiers -- Part IV: Advanced Topics -- Beyond Sparsity -- Appendix A: Mathematics -- Appendix B: Computer Programming Resources for Sparse Recovery Approaches -- Appendix C: The source Code of Sparsity Induced Similarity -- Appendix D: Derivations.

This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: Provides a thorough introduction to the fundamentals of sparse representation, modeling and learning, and the application of these techniques in visual recognition Describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition Covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers Discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning Includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book Researchers and graduate students interested in computer vision, pattern recognition and robotics will find this work to be an invaluable introduction to techniques of sparse representations and compressive sensing. Dr. Hong Cheng is Professor in the School of Automation Engineering, and Deputy Executive Director of the Center for Robotics at the University of Electronic Science and Technology of China. His other publications include the Springer book Autonomous Intelligent Vehicles.

ISBN: 9781447167143 (electronic bk.)

Standard No.: 10.1007/978-1-4471-6714-3doiSubjects--Topical Terms:

200113
Computer vision.

LC Class. No.: TA1634

Dewey Class. No.: 006.42

Sparse representation, modeling and learning in visual recognitiontheory, algorithms and applications /
LDR:03325nmm a2200325 a 4500 001 468924
003 DE-He213
005 20151216171453.0
006 m d
007 cr nn 008maaau
008 160118s2015 enk s 0 eng d
020 $a 9781447167143 (electronic bk.)
020 $a 9781447167136 (paper)
024 7 $a 10.1007/978-1-4471-6714-3 $2 doi
035 $a 978-1-4471-6714-3
040 $a GP $c GP
041 0 $a eng
050 4 $a TA1634
072 7 $a UYQP $2 bicssc
072 7 $a COM016000 $2 bisacsh
082 0 4 $a 006.42 $2 23
090 $a TA1634 $b .C518 2015
100 1 $a Cheng, Hong. $3 539342
245 1 0 $a Sparse representation, modeling and learning in visual recognition $h [electronic resource] : $b theory, algorithms and applications / $c by Hong Cheng.
260 $a London : $b Springer London : $b Imprint: Springer, $c 2015.
300 $a xiv, 257 p. : $b ill., digital ; $c 24 cm.
490 1 $a Advances in computer vision and pattern recognition, $x 2191-6586
505 0 $a Part I: Introduction and Fundamentals -- Introduction -- The Fundamentals of Compressed Sensing -- Part II: Sparse Representation, Modeling and Learning -- Sparse Recovery Approaches -- Robust Sparse Representation, Modeling and Learning -- Efficient Sparse Representation and Modeling -- Part III: Visual Recognition Applications -- Feature Representation and Learning -- Sparsity Induced Similarity -- Sparse Representation and Learning Based Classifiers -- Part IV: Advanced Topics -- Beyond Sparsity -- Appendix A: Mathematics -- Appendix B: Computer Programming Resources for Sparse Recovery Approaches -- Appendix C: The source Code of Sparsity Induced Similarity -- Appendix D: Derivations.
520 $a This unique text/reference presents a comprehensive review of the state of the art in sparse representations, modeling and learning. The book examines both the theoretical foundations and details of algorithm implementation, highlighting the practical application of compressed sensing research in visual recognition and computer vision. Topics and features: Provides a thorough introduction to the fundamentals of sparse representation, modeling and learning, and the application of these techniques in visual recognition Describes sparse recovery approaches, robust and efficient sparse representation, and large-scale visual recognition Covers feature representation and learning, sparsity induced similarity, and sparse representation and learning-based classifiers Discusses low-rank matrix approximation, graphical models in compressed sensing, collaborative representation-based classification, and high-dimensional nonlinear learning Includes appendices outlining additional computer programming resources, and explaining the essential mathematics required to understand the book Researchers and graduate students interested in computer vision, pattern recognition and robotics will find this work to be an invaluable introduction to techniques of sparse representations and compressive sensing. Dr. Hong Cheng is Professor in the School of Automation Engineering, and Deputy Executive Director of the Center for Robotics at the University of Electronic Science and Technology of China. His other publications include the Springer book Autonomous Intelligent Vehicles.
650 0 $a Computer vision. $3 200113
650 0 $a Visual perception. $3 205511
650 0 $a Image processing. $3 182627
650 0 $a Signal processing $x Digital techniques $x Mathematics. $3 184837
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Pattern Recognition. $3 273706
650 2 4 $a Image Processing and Computer Vision. $3 274051
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 252959
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Advances in computer vision and pattern recognition. $3 559645
856 4 0 $u http://dx.doi.org/10.1007/978-1-4471-6714-3
950 $a Computer Science (Springer-11645)