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Erschienen in:
Adaptation Approaches in Unsupervised Learning: A Survey of the State-of-the-Art and Future Directions Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

Person Profiling Using Image and Facial Attributes Analyses on Unconstrained Images Retrieved from Online Sources

verfasst von : Elisabeth Wetzinger, Michael Atanasov, Martin Kampel

Erschienen in: Image Analysis and Recognition

Verlag: Springer International Publishing

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Abstract

With the existence and growth of Social Network Services (SNS), they have become focus in data and image processing research and concerning their potential to describe persons based on online available information. In this paper we propose a novel approach for person profiling solely based on images for children and adolescents of age 10+. The application acquires pictures from search engines and SNS and performs image-based analysis focusing on facial attributes. Image analysis results using different image datasets are presented showing that image analytics faces challenges of its application unconstrained datasets, but has the potential to push SNS analytics to a new level of detail in people profiling. The applications aims at improving the target users’ media literacy, raising their awareness for risks and consequences and at encouraging them in dealing responsibly with pictures online.

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Vorheriges Kapitel Combining Low-Level Features of Offline Questionnaires for Handwriting Identification
Nächstes Kapitel Palm Print Identification and Verification Using a Genetic-Based Feature Extraction Technique
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Metadaten
Titel
Person Profiling Using Image and Facial Attributes Analyses on Unconstrained Images Retrieved from Online Sources
verfasst von
Elisabeth Wetzinger
Michael Atanasov
Martin Kampel
Copyright-Jahr
2016
Buch
Image Analysis and Recognition

Print ISBN: 978-3-319-41500-0

Electronic ISBN: 978-3-319-41501-7

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-41501-7_7