Jia Jia
ABSTRACT
Can we understand van Gogh's mood from his artworks? For many years, people have tried to capture van Gogh's affects from his artworks so as to understand the essential meaning behind the images and catch on why van Gogh created these works. In this paper, we study the problem of inferring affects from images in social networks. In particular, we aim to answer: What are the fundamental features that reflect the affects of the authors in images? How the social network information can be leveraged to help detect these affects? We propose a semi-supervised framework to formulate the problem into a factor graph model. Experiments on 20,000 random-download Flickr images show that our method can achieve a precision of 49% with a recall of 24% on inferring authors'affects into 16 categories. Finally, we demonstrate the effectiveness of the proposed method on automatically understanding van Gogh's Mood from his artworks, and inferring the trend of public affects around special event.
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Index Terms
- Can we understand van gogh's mood?: learning to infer affects from images in social networks
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