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Mastering OpenCV 3

You're reading from   Mastering OpenCV 3 Get hands-on with practical Computer Vision using OpenCV 3

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Product type Paperback
Published in Apr 2017
Publisher
ISBN-13 9781786467171
Length 250 pages
Edition 2nd Edition
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Authors (6):
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Shervin Emami Shervin Emami
Author Profile Icon Shervin Emami
Shervin Emami
David Millán Escrivá David Millán Escrivá
Author Profile Icon David Millán Escrivá
David Millán Escrivá
Eugene Khvedchenia Eugene Khvedchenia
Author Profile Icon Eugene Khvedchenia
Eugene Khvedchenia
Daniel Lelis Baggio Daniel Lelis Baggio
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Daniel Lelis Baggio
Roy Shilkrot Roy Shilkrot
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Roy Shilkrot
Jason Saragih Jason Saragih
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Jason Saragih
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Toc

Facial feature detectors


Detecting facial features in images bares a strong resemblance to general object detection. OpenCV has a set of sophisticated functions for building general object detectors, the most well-known of which is the cascade of Haar-based feature detectors used in their implementation of the well-known Viola-Jones face detector. There are, however, a few distinguishing factors that make facial feature detection unique. These are as follows:

  • Precision versus robustness: In generic object detection, the aim is to find the coarse position of the object in the image; facial feature detectors are required to give highly precise estimates of the location of the feature. An error of a few pixels is considered inconsequential in object detection but it can mean the difference between a smile and a frown in facial expression estimation through feature detections.
  • Ambiguity from limited spatial support: It is common to assume that the object of interest in generic object detection...
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