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Mastering OpenCV with Practical Computer Vision Projects

You're reading from   Mastering OpenCV with Practical Computer Vision Projects This is the definitive advanced tutorial for OpenCV, designed for those with basic C++ skills. The computer vision projects are divided into easily assimilated chapters with an emphasis on practical involvement for an easier learning curve.

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Product type Paperback
Published in Dec 2012
Publisher Packt
ISBN-13 9781849517829
Length 340 pages
Edition 1st Edition
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Table of Contents (15) Chapters Close

Mastering OpenCV with Practical Computer Vision Projects
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Cartoonifier and Skin Changer for Android FREE CHAPTER 2. Marker-based Augmented Reality on iPhone or iPad 3. Marker-less Augmented Reality 4. Exploring Structure from Motion Using OpenCV 5. Number Plate Recognition Using SVM and Neural Networks 6. Non-rigid Face Tracking 7. 3D Head Pose Estimation Using AAM and POSIT 8. Face Recognition using Eigenfaces or Fisherfaces Index

References


  • Rapid Object Detection using a Boosted Cascade of Simple Features, P. Viola and M.J. Jones, Proceedings of the IEEE Transactions on CVPR 2001, Vol. 1, pp. 511-518

  • An Extended Set of Haar-like Features for Rapid Object Detection, R. Lienhart and J. Maydt, Proceedings of the IEEE Transactions on ICIP 2002, Vol. 1, pp. 900-903

  • Face Description with Local Binary Patterns: Application to Face Recognition, T. Ahonen, A. Hadid and M. Pietikäinen, Proceedings of the IEEE Transactions on PAMI 2006, Vol. 28, Issue 12, pp. 2037-2041

  • Learning OpenCV: Computer Vision with the OpenCV Library, G. Bradski and A. Kaehler, pp. 186-190, O'Reilly Media.

  • Eigenfaces for recognition, M. Turk and A. Pentland, Journal of Cognitive Neuroscience 3, pp. 71-86

  • Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection, P.N. Belhumeur, J. Hespanha and D. Kriegman, Proceedings of the IEEE Transactions on PAMI 1997, Vol. 19, Issue 7, pp. 711–720

  • Face Recognition with Local Binary Patterns...

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