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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

Face detection and initialization


The method for face tracking described thus far has assumed that the facial features in the image are located within a reasonable proximity to the current estimate. Although this assumption is reasonable during tracking, where face motion between frames is often quite small, we are still faced with the dilemma of how to initialize the model in the first frame of the sequence. An obvious choice for this is to use OpenCV's in-built cascade detector to find the face. However, the placement of the model within the detected bounding box will depend on the selection made for the facial features to track. In keeping with the data-driven paradigm we have followed so far in this chapter, a simple solution is to learn the geometrical relationship between the face detection's bounding box and the facial features.

The face_detector class implements exactly this solution. A snippet of its declaration that highlights its functionality is given as follows:

class face_detector...
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