Coverart for item
The Resource Person re-identification, Shaogang Gong, Marco Cristani, Shuicheng Yan, Chen Change Loy, editors, (electronic resource)

Person re-identification, Shaogang Gong, Marco Cristani, Shuicheng Yan, Chen Change Loy, editors, (electronic resource)

Label
Person re-identification
Title
Person re-identification
Statement of responsibility
Shaogang Gong, Marco Cristani, Shuicheng Yan, Chen Change Loy, editors
Contributor
Subject
Language
eng
Summary
  • Re-identification offers a useful tool for non-invasive biometric validation, surveillance, and human-robot interaction in a broad range of applications from crowd traffic management to personalised healthcare. This comprehensive volume is the first work of its kind dedicated to addressing the challenge of Person Re-Identification, presenting insights from an international selection of leading authorities in the field. Taking a strongly multidisciplinary approach, the text provides an in-depth discussion of recent developments and state-of-the-art methods drawn from the computer vision, pattern recognition and machine learning communities, embracing both fundamental research and practical applications. Topics and features: Introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms, and examines the benefits of semantic attributes. Describes how to segregate meaningful body parts from background clutter. Examines the use of 3D depth images, and contextual constraints derived from the visual appearance of a group. Reviews approaches to feature transfer function and distance metric learning, and discusses potential solutions to issues of data scalability and identity inference. Investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference, and describes techniques for improving post-rank search efficiency. Explores the design rationale and implementation considerations of building a practical re-identification system. This timely collection will be of great interest to academics, industrial researchers and postgraduates involved in computer vision and machine learning, database image retrieval, big data mining, and search engines, as well as to developers keen to exploit this emerging technology for commercial applications. --
  • Re-identification offers a useful tool for non-invasive biometric validation, surveillance, and human-robot interaction in a broad range of applications from crowd traffic management to personalised healthcare. This comprehensive volume is the first work of its kind dedicated to addressing the challenge of Person Re-Identification, presenting insights from an international selection of leading authorities in the field. Taking a strongly multidisciplinary approach, the text provides an in-depth discussion of recent developments and state-of-the-art methods drawn from the computer vision, pattern recognition and machine learning communities, embracing both fundamental research and practical applications. Topics and features: Introduces examples of robust feature representations, reviews salient feature weighting and selection mechanisms, and examines the benefits of semantic attributes. Describes how to segregate meaningful body parts from background clutter. Examines the use of 3D depth images, and contextual constraints derived from the visual appearance of a group. Reviews approaches to feature transfer function and distance metric learning, and discusses potential solutions to issues of data scalability and identity inference. Investigates the limitations of existing benchmark datasets, presents strategies for camera topology inference, and describes techniques for improving post-rank search efficiency. Explores the design rationale and implementation considerations of building a practical re-identification system. This timely collection will be of great interest to academics, industrial researchers and postgraduates involved in computer vision and machine learning, database image retrieval, big data mining, and search engines, as well as to developers keen to exploit this emerging technology for commercial applications. --
Member of
Assigning source
  • Source other than Library of Congress
  • Source other than Library of Congress
Cataloging source
BTCTA
LC call number
TK7882.P3
LC item number
P468 2014
http://library.link/vocab/relatedWorkOrContributorName
  • Gong, Shaogang
  • Cristani, Marco
  • Yan, Shuicheng
  • Loy, Chen Change
Series statement
Advances in computer vision and pattern recognition,
http://library.link/vocab/subjectName
  • Pattern recognition systems
  • Computer vision
  • Video surveillance
  • Biometric identification
  • Digital video
  • Biometric identification
  • Computer vision
  • Digital video
  • Pattern recognition systems
  • Video surveillance
Label
Person re-identification, Shaogang Gong, Marco Cristani, Shuicheng Yan, Chen Change Loy, editors, (electronic resource)
Instantiates
Publication
Bibliography note
Includes bibliographical references and index
Control code
OCM1bookssj0001165591
Dimensions
unknown
Isbn
9781447162957
Isbn Type
(alk. paper)
Lccn
2013957125
Note
Electronic reproduction. Palo Alto, Calif. : ebrary, 2014. Available via World Wide Web. Access may be limited to ebrary affiliated libraries.
Specific material designation
remote
System control number
(WaSeSS)bookssj0001165591
Label
Person re-identification, Shaogang Gong, Marco Cristani, Shuicheng Yan, Chen Change Loy, editors, (electronic resource)
Publication
Bibliography note
Includes bibliographical references and index
Control code
OCM1bookssj0001165591
Dimensions
unknown
Isbn
9781447162957
Isbn Type
(alk. paper)
Lccn
2013957125
Note
Electronic reproduction. Palo Alto, Calif. : ebrary, 2014. Available via World Wide Web. Access may be limited to ebrary affiliated libraries.
Specific material designation
remote
System control number
(WaSeSS)bookssj0001165591

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      38.710138 -90.311107
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