Paper in IJCNN (2017) "Towards Using Visual Attributes to Infer Image Sentiment Of Social Events"

Paper

  • U. Ahsan, M. D. Choudhury, and Irfan Essa (2017), “Towards Using Visual Attributes to Infer Image Sentiment Of Social Events,” in Proceedings of The International Joint Conference on Neural Networks, Anchorage, Alaska, US, 2017. [PDF] [BIBTEX]
    @InProceedings{ 2017-Ahsan-TUVAIISSE,
    address  = {Anchorage, Alaska, US},
    author  = {Unaiza Ahsan and Munmun De Choudhury and Irfan
    Essa},
    booktitle  = {Proceedings of The International Joint Conference
    on Neural Networks},
    month = {May},
    pdf = {http://www.cc.gatech.edu/~irfan/p/2017-Ahsan-TUVAIISSE.pdf},
    publisher  = {International Neural Network Society},
    title = {Towards Using Visual Attributes to Infer Image
    Sentiment Of Social Events},
    year = {2017}
    }

Abstract

Widespread and pervasive adoption of smartphones has led to instant sharing of photographs that capture events ranging from mundane to life-altering happenings. We propose to capture sentiment information of such social event images leveraging their visual content. Our method extracts an intermediate visual representation of social event images based on the visual attributes that occur in the images going beyond
sentiment-specific attributes. We map the top predicted attributes to sentiments and extract the dominant emotion associated with a picture of a social event. Unlike recent approaches, our method generalizes to a variety of social events and even to unseen events, which are not available at training time. We demonstrate the effectiveness of our approach on a challenging social event image dataset and our method outperforms state-of-the-art approaches for classifying complex event images into sentiments.

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