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Visual Persuasion

Visual Persuasion: Inferring Communicative Intents of Images

Jungseock Joo, Weixin Li, Francis F. Steen, and Song-Chun Zhu

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014. [pdf] 


- Is a Picture Worth 1,000 Polls? by Virginia Postrel. Bloomberg View. June 25, 2014.


In this paper we introduce the novel problem of understanding visual persuasion. Modern mass media and advertising make extensive use of images and video to present arguments and influence public opinion, and their techniques are widely studied in media research, political science, and psychology, typically using small, hand-coded datasets. We propose to extend the significant advances in syntactic analyses, such as the detection and identification of objects and sentiments in images and video, to the higher-level challenge of understanding the underlying communicative intent implied in the images. We define the problem of inferring communicative intents from images in a computational framework, and demonstrate the feasibility of progress in a case study from politics, a domain of intense competitive persuasion with continuously measurable outcomes in opinion polls. The quantitative results demonstrate that a systematic focus on visual persuasion opens up the field of computer vision to a new class of investigations around mediated images, intersecting with media analysis, psychology, and political communication.

Spotlight Presentation

Dataset - Persuasive Portraits of Politicians

Our dataset contains 1,124 photographs of 8 US politicians. Each image was labeled with 9 intent dimensions as well as 15 syntactical attributes. The annotation can be freely used for academic purpose. Please contact Jungseock for the full access.