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Low-Resource Speech Recognition and Keyword-Spotting Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Semi-automatic Facial Key-Point Dataset Creation

Authors : Miroslav Hlaváč, Ivan Gruber, Miloš Železný, Alexey Karpov

Published in: Speech and Computer

Publisher: Springer International Publishing

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Abstract

This paper presents a semi-automatic method for creating a large scale facial key-point dataset from a small number of annotated images. The method consists of annotating the facial images by hand, training Active Appearance Model (AAM) from the annotated images and then using the AAM to annotate a large number of additional images for the purpose of training a neural network. The images from the AAM are then re-annotated by the neural network and used to validate the precision of the proposed neural network detections. The neural network architecture is presented including the training parameters.

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previous chapter Retaining Expression on De-identified Faces
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Metadata
Title
Semi-automatic Facial Key-Point Dataset Creation
Authors
Miroslav Hlaváč
Ivan Gruber
Miloš Železný
Alexey Karpov
Copyright Year
2017
Book
Speech and Computer

Print ISBN: 978-3-319-66428-6

Electronic ISBN: 978-3-319-66429-3

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-66429-3_66

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