Challenges and Limitations Concerning Automatic Child Pornography Classification

Anton Moser; Marlies Rybnicek; Daniel Haslinger

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Paper

Challenges and Limitations Concerning Automatic Child Pornography Classification

Topics: Categorization and Scene Understanding; Content-Based Indexing, Search, and Retrieval; Face and Expression Recognition; Machine Learning Technologies for Vision; Object and Face Recognition; Object Detection and Localization

In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, 492-497, 2015 , Berlin, Germany

Authors: Anton Moser ; Marlies Rybnicek and Daniel Haslinger

Affiliation: St. Poelten University of Applied Sciences, Austria

Keyword(s): Computer Vision, Automated Child Pornography Detection, Content Classification.

Abstract: The huge volume of data to be analyzed in the course of child pornography investigations puts special demands on tools and methods for automated classification, often used by law enforcement and prosecution. The need for a clear distinction between pornographic material and inoffensive pictures with a large amount of skin, like people wearing bikinis or underwear, causes problems. Manual evaluation carried out by humans tends to be impossible due to the sheer number of assets to be sighted. The main contribution of this paper is an overview of challenges and limitations encountered in the course of automated classification of image data. An introduction of state-of-the-art methods, including face- and skin tone detection, face- and texture recognition as well as craniofacial growth evaluation is provided. Based on a prototypical implementation of feasible and promising approaches, the performance is evaluated, as well as their abilities and shortcomings.

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Paper citation in several formats:

Moser, A.; Rybnicek, M. and Haslinger, D. (2015). Challenges and Limitations Concerning Automatic Child Pornography Classification. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 492-497. DOI: 10.5220/0005344904920497

@conference{visapp15,
author={Anton Moser. and Marlies Rybnicek. and Daniel Haslinger.},
title={Challenges and Limitations Concerning Automatic Child Pornography Classification},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP},
year={2015},
pages={492-497},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005344904920497},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP
TI - Challenges and Limitations Concerning Automatic Child Pornography Classification
SN - 978-989-758-090-1
IS - 2184-4321
AU - Moser, A.
AU - Rybnicek, M.
AU - Haslinger, D.
PY - 2015
SP - 492
EP - 497
DO - 10.5220/0005344904920497
PB - SciTePress