MARC details
| 000 -LEADER |
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05863nam a22004935i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
978-0-85729-057-1 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251006084442.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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101119s2011 xxk| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780857290571 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
99780857290571 |
| 024 7# - OTHER STANDARD IDENTIFIER |
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| Standard number or code |
10.1007/978-0-85729-057-1 |
| Source of number or code |
doi |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.6 |
| Edition information |
23 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.37 |
| Edition information |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Wang, Liang. |
| Relator term |
editor. |
| 245 10 - TITLE STATEMENT |
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| Title |
Machine Learning for Vision-Based Motion Analysis |
| Medium |
[electronic resource] : |
| Remainder of title |
Theory and Techniques / |
| Statement of responsibility, etc. |
edited by Liang Wang, Guoying Zhao, Li Cheng, Matti Pietikäinen. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
London : |
| Name of producer, publisher, distributor, manufacturer |
Springer London : |
| -- |
Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2011. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
XIV, 372 p. |
| Other physical details |
online resource. |
| 336 ## - CONTENT TYPE |
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| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
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| File type |
text file |
| Encoding format |
PDF |
| Source |
rda |
| 490 1# - SERIES STATEMENT |
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| Series statement |
Advances in Pattern Recognition, |
| International Standard Serial Number |
2191-6586 |
| 505 0# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Part I: Manifold Learning and Clustering/Segmentation -- Practical Algorithms of Spectral Clustering: Toward Large-Scale Vision-Based Motion Analysis -- Riemannian Manifold Clustering and Dimensionality Reduction for Vision-based Analysis -- Manifold Learning for Multi-dimensional Auto-regressive Dynamical Models -- Part II: Tracking -- Mixed-state Markov Models in Image Motion Analysis -- Learning to Detect Event Sequences in Surveillance Streams at Very Low Frame Rate -- Discriminative Multiple Target Tracking -- A Framework of Wire Tracking in Image Guided Interventions -- Part III: Motion Analysis and Behavior Modeling -- An Integrated Approach to Visual Attention Modeling for Saliency Detection in Videos -- Video-based Human Motion Estimation by Part-whole Gait Manifold Learning -- Spatio-temporal Motion Pattern Models of Extremely Crowded Scenes -- Learning Behavioral Patterns of Time Series for Video-surveillance -- Part IV: Gesture and Action Recognition -- Recognition of Spatiotemporal Gestures in Sign Language using Gesture Threshold HMMs -- Learning Transferable Distance Functions for Human Action Recognition. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Techniques of vision-based motion analysis aim to detect, track, identify, and generally understand the behavior of objects in image sequences. With the growth of video data in a wide range of applications from visual surveillance to human-machine interfaces, the ability to automatically analyze and understand object motions from video footage is of increasing importance. Among the latest developments in this field is the application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions to the first and second International Workshop on Machine Learning for Vision-Based Motion Analysis, this important text/reference highlights the latest algorithms and systems for robust and effective vision-based motion understanding from a machine learning perspective. Highlighting the benefits of collaboration between the communities of object motion understanding and machine learning, the book discusses the most active forefronts of research, including current challenges and potential future directions. Topics and features: Provides a comprehensive review of the latest developments in vision-based motion analysis, presenting numerous case studies on state-of-the-art learning algorithms Examines algorithms for clustering and segmentation, and manifold learning for dynamical models Describes the theory behind mixed-state statistical models, with a focus on mixed-state Markov models that take into account spatial and temporal interaction Discusses object tracking in surveillance image streams, discriminative multiple target tracking, and guidewire tracking in fluoroscopy Explores issues of modeling for saliency detection, human gait modeling, modeling of extremely crowded scenes, and behavior modeling from video surveillance data Investigates methods for automatic recognition of gestures in Sign Language, and human action recognition from small training sets Researchers, professional engineers, and graduate students in computer vision, pattern recognition and machine learning, will all find this text an accessible survey of machine learning techniques for vision-based motion analysis. The book will also be of interest to all who work with specific vision applications, such as surveillance, sport event analysis, healthcare, video conferencing, and motion video indexing and retrieval. Dr. Liang Wang is a lecturer at the Department of Computer Science at the University of Bath, UK, and is also affiliated to the National Laboratory of Pattern Recognition in Beijing, China. Dr. Guoying Zhao is an adjunct professor at the Department of Electrical and Information Engineering at the University of Oulu, Finland. Dr. Li Cheng is a research scientist at the Agency for Science, Technology and Research (A*STAR), Singapore. Dr. Matti Pietikäinen is Professor of Information Technology at the Department of Electrical and Information Engineering at the University of Oulu, Finland. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
COMPUTER SCIENCE. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
ARTIFICIAL INTELLIGENCE. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
COMPUTER VISION. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
COMPUTER SCIENCE. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
IMAGE PROCESSING AND COMPUTER VISION. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
ARTIFICIAL INTELLIGENCE (INCL. ROBOTICS). |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Zhao, Guoying. |
| Relator term |
editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Cheng, Li. |
| Relator term |
editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Pietikäinen, Matti. |
| Relator term |
editor. |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
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| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
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| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
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| Relationship information |
Printed edition: |
| International Standard Book Number |
9780857290564 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
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| Uniform title |
Advances in Pattern Recognition, |
| International Standard Serial Number |
2191-6586 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
<a href="http://dx.doi.org/10.1007/978-0-85729-057-1">http://dx.doi.org/10.1007/978-0-85729-057-1</a> |
| Public note |
Ver el texto completo en las instalaciones del CICY |
| 912 ## - |
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| -- |
ZDB-2-SCS |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Libros electrónicos |
