SAIVT-ADMRG @ MediaEval 2014 Social Event Detection
Simon Denman, David B. Dean, Clinton Fookes, Sridha Sridharan · QUT ePrints (Queensland University of Technology) · 2014
This paper outlines the approach taken by the Speech, Au-dio, Image and Video Technologies laboratory, and the Ap-plied Data Mining Research Group (SAIVT-ADMRG) in the 2014 MediaEval Social Event Detection (SED) task. We participated in the event based clustering subtask (subtask 1), and focused on investigating the incorporation of image features as another source of data to aid clustering. In par-ticular, we developed a descriptor based around the use of super-pixel segmentation, that allows a low dimensional fea-ture that incorporates both colour and texture information to be extracted and used within the popular bag-of-visual-words (BoVW) approach. 1.