%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/08.31.17.25
%2 sid.inpe.br/sibgrapi/2016/08.31.17.25.01
%T Organizing Images from Social Media to Monitor Real-World Events
%D 2016
%A Cavalin, Paulo,
%A Figueiredo, Flavio,
%A Bayser, Maira de,
%A Pinhanez, Claudio,
%@affiliation IBM Research
%@affiliation IBM Research
%@affiliation IBM Research
%@affiliation IBM Research
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I Sociedade Brasileira de Computação
%J Porto Alegre
%S Proceedings
%K Social Media, Image Summarization, Image Similarity.
%X Everyday, millions of images are posted in social media websites online. Given that in social media websites there are no guarantees of image precedence and quality, making sense of social media imagery presents itself as a challenging task. In this paper, we describe the architecture of a system developed to facilitate the analysis of social media imagery. Our system combines both low-level and high-level image analytics to organize the images into a reduced and semantically-linked set that can be explored by end-users. We evaluate our system on a large dataset of images posted during major social media events such as the 2014 World Cup Finals.
%@language en
%3 SibgrapiWIA2016_cameraready.pdf