The Resource Human action recognition with depth cameras, Jiang Wang, Zicheng Liu, Ying Wu

Human action recognition with depth cameras, Jiang Wang, Zicheng Liu, Ying Wu

Label
Human action recognition with depth cameras
Title
Human action recognition with depth cameras
Statement of responsibility
Jiang Wang, Zicheng Liu, Ying Wu
Creator
Contributor
Author
Provider
Subject
Language
eng
Summary
Action recognition is an enabling technology for many real world applications, such as human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. In the past decade, it has attracted a great amount of interest in the research community. Recently, the commoditization of depth sensors has generated much excitement in action recognition from depth sensors. New depth sensor technology has enabled many applications that were not feasible before. On one hand, action recognition becomes far easier with depth sensors. On the other hand, the drive to recognize more complex actions presents new challenges. One crucial aspect of action recognition is to extract discriminative features. The depth maps have completely different characteristics from the RGB images. Directly applying features designed for RGB images does not work. Complex actions usually involve complicated temporal structures, human-object interactions, and person-person contacts. New machine learning algorithms need to be developed to learn these complex structures. This work enables the reader to quickly familiarize themselves with the latest research in depth-sensor based action recognition, and to gain a deeper understanding of recently developed techniques. It will be of great use for both researchers and practitioners who are interested in human action recognition with depth sensors. The text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art in action recognition from depth data, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, including lower-level depth and skeleton features, higher-level representations to model the temporal structure and human-object interactions, and feature selection techniques for occlusion handling
Member of
Cataloging source
N$T
http://library.link/vocab/creatorName
Wang, Jiang
Image bit depth
0
LC call number
TK7882.P7
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorDate
1973-
http://library.link/vocab/relatedWorkOrContributorName
  • SpringerLink
  • Liu, Zicheng
  • Wu, Ying
Series statement
SpringerBriefs in Computer Science,
http://library.link/vocab/subjectName
  • Human activity recognition
  • Proximity detectors
  • Cameras
  • TECHNOLOGY & ENGINEERING / Technical & Manufacturing Industries & Trades
  • Cameras
  • Human activity recognition
  • Proximity detectors
Label
Human action recognition with depth cameras, Jiang Wang, Zicheng Liu, Ying Wu
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction -- Learning Actionlet Ensemble for 3D Human Action Recognition -- Random Occupancy Patterns -- Conclusion
Dimensions
unknown
Extent
1 online resource
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9783319045610
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
  • (OCoLC)871325580
  • (OCoLC)ocn871325580
Label
Human action recognition with depth cameras, Jiang Wang, Zicheng Liu, Ying Wu
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction -- Learning Actionlet Ensemble for 3D Human Action Recognition -- Random Occupancy Patterns -- Conclusion
Dimensions
unknown
Extent
1 online resource
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9783319045610
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
  • (OCoLC)871325580
  • (OCoLC)ocn871325580

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