3D Face Modeling, Analysis and Recognition (ePub)
(Sprache: Englisch)
3D Face Modeling, Analysis and Recognition presents
methodologies for analyzing shapes of facial surfaces, develops
computational tools for analyzing 3D face data, and illustrates
them using state-of-the-art applications. The methodologies chosen
are...
methodologies for analyzing shapes of facial surfaces, develops
computational tools for analyzing 3D face data, and illustrates
them using state-of-the-art applications. The methodologies chosen
are...
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Produktinformationen zu „3D Face Modeling, Analysis and Recognition (ePub)“
3D Face Modeling, Analysis and Recognition presents
methodologies for analyzing shapes of facial surfaces, develops
computational tools for analyzing 3D face data, and illustrates
them using state-of-the-art applications. The methodologies chosen
are based on efficient representations, metrics, comparisons, and
classifications of features that are especially relevant in the
context of 3D measurements of human faces. These frameworks have a
long-term utility in face analysis, taking into account the
anticipated improvements in data collection, data storage,
processing speeds, and application scenarios expected as the
discipline develops further.
The book covers face acquisition through 3D scanners and 3D face
pre-processing, before examining the three main approaches for 3D
facial surface analysis and recognition: facial curves; facial
surface features; and 3D morphable models. Whilst the focus of
these chapters is fundamentals and methodologies, the algorithms
provided are tested on facial biometric data, thereby continually
showing how the methods can be applied.
Key features:
* Explores the underlying mathematics and will apply these
mathematical techniques to 3D face analysis and recognition
* Provides coverage of a wide range of applications including
biometrics, forensic applications, facial expression analysis, and
model fitting to 2D images
* Contains numerous exercises and algorithms throughout the
book
methodologies for analyzing shapes of facial surfaces, develops
computational tools for analyzing 3D face data, and illustrates
them using state-of-the-art applications. The methodologies chosen
are based on efficient representations, metrics, comparisons, and
classifications of features that are especially relevant in the
context of 3D measurements of human faces. These frameworks have a
long-term utility in face analysis, taking into account the
anticipated improvements in data collection, data storage,
processing speeds, and application scenarios expected as the
discipline develops further.
The book covers face acquisition through 3D scanners and 3D face
pre-processing, before examining the three main approaches for 3D
facial surface analysis and recognition: facial curves; facial
surface features; and 3D morphable models. Whilst the focus of
these chapters is fundamentals and methodologies, the algorithms
provided are tested on facial biometric data, thereby continually
showing how the methods can be applied.
Key features:
* Explores the underlying mathematics and will apply these
mathematical techniques to 3D face analysis and recognition
* Provides coverage of a wide range of applications including
biometrics, forensic applications, facial expression analysis, and
model fitting to 2D images
* Contains numerous exercises and algorithms throughout the
book
Autoren-Porträt von Mohamed Daoudi, Anuj Srivastava, Remco Veltkamp
Mohamed Daoudi, TELECOM Lille 1, France Professor Daoudiis a member of the computer science department at TELECOM Lille 1,
and a member of the IEEE. Prof. Daoudi is an editor of the Journal
of Multimedia and has been a guest co-editor of the Annals of
Telecommunications for a special issue on Technologies and Tools
for 3D Imaging. He co-edited 3D Object Processing: Compression,
Indexing and Watermarking published by Wiley in 2008.
Anuj Srivastava, Florida State University, USA Professor
Srivastava is a member of the department of statistics at Florida
State University, and a member of the IEEE and ASA. He has been an
associate editor of the Journal of Statistical Planning and
Interference, IEEE Transactions on Signal Processing, and IEEE
Transactions on Pattern Analysis and Machine Intelligence, which he
also edited a special issue of on Shape Modeling. He has published
over 30 journal papers and 7 book chapters in edited volumes.
Remco Veltkamp, Universiteit Utrecht, The Netherlands
Professor Veltkamp is a member of the department of Information and
Computing Sciences at Utrecht University, focusing on multimedia
applications. He is an editor of Pattern Recognition Journal and
the International Journal on Shape Modeling. He has also guest
edited several journals including a special issue on Multimedia
Algorithmics in Multimedia Tools and Applications, and a
special issue on Shape Reasoning and Understanding in Computers
& Graphics. Prof. Veltkamp has published 30 journal papers, 13
book chapters in edited volumes, co-edited several conference
proceedings and has co-edited State-of-the-art in Content-based
Image and Video Retrieval published by Springer in 2001.
Bibliographische Angaben
- Autoren: Mohamed Daoudi , Anuj Srivastava , Remco Veltkamp
- 2013, 1. Auflage, 224 Seiten, Englisch
- Verlag: John Wiley & Sons
- ISBN-10: 1118592638
- ISBN-13: 9781118592632
- Erscheinungsdatum: 11.06.2013
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eBook Informationen
- Dateiformat: ePub
- Größe: 5.57 MB
- Mit Kopierschutz
Sprache:
Englisch
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