Uncovering Scene Context for Predicting Privacy of Online Shared Images

Authors

  • Ashwini Tonge Kansas State University
  • Cornelia Caragea Kansas State Univeristy
  • Anna Squicciarini Pennsylvania State University

Keywords:

image privacy prediction, scene tags, object tags, Convolutional neural networks, social media, image tagging

Abstract

With the exponential increase in the number of images that are shared online every day, the development of effective and efficient learning methods for image privacy prediction has become crucial. Prior works have used as features automatically derived object tags from images' content and manually annotated user tags. However, we believe that in addition to objects, the scene context obtained from images’ content can improve the performance of privacy prediction. Hence, we propose to uncover scene-based tags from images' content using convolutional neural networks. Experimental results on a Flickr dataset show that the scene tags and object tags complement each other and yield the best performance when used in combination with user tags.

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Published

2018-04-29

How to Cite

Tonge, A., Caragea, C., & Squicciarini, A. (2018). Uncovering Scene Context for Predicting Privacy of Online Shared Images. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/12180