Items related to Probabilistic Graphical Models for Computer Vision.

Probabilistic Graphical Models for Computer Vision. - Hardcover

Ji, Qiang

 
9780128034675: Probabilistic Graphical Models for Computer Vision.
Hardcover
ISBN 10: 012803467X ISBN 13: 9780128034675
Publisher: Academic Press, 2019

Synopsis

Probabilistic Graphical Models for Computer Vision introduces probabilistic graphical models (PGMs) for computer vision problems and teaches how to develop the PGM model from training data. This book discusses PGMs and their significance in the context of solving computer vision problems, giving the basic concepts, definitions and properties. It also provides a comprehensive introduction to well-established theories for different types of PGMs, including both directed and undirected PGMs, such as Bayesian Networks, Markov Networks and their variants.

  • Discusses PGM theories and techniques with computer vision examples
  • Focuses on well-established PGM theories that are accompanied by corresponding pseudocode for computer vision
  • Includes an extensive list of references, online resources and a list of publicly available and commercial software
  • Covers computer vision tasks, including feature extraction and image segmentation, object and facial recognition, human activity recognition, object tracking and 3D reconstruction

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About the Author

Qiang Ji is in the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute, New York, USA

"About this title" may belong to another edition of this title.

Publisher
Academic Press
Publication date
2019
Language
English
ISBN 10 
012803467X
ISBN 13 
9780128034675
Binding
Hardcover
Edition number
1
Number of pages
294