Research & Contributions
This paper provides an overview of the Predicting MediaInterestingness task that is organized as part of the Media-Eval 2016 Benchmarking Initiative for Multimedia Evalua-tion. The task, which is running for the first year, expectsparticipants to create systems that automatically select images and video segments that are considered to be the mostinteresting for a common viewer. In this paper, we presentthe task use case and challenges, the proposed data set andground truth, the required participant runs and the evalua-tion metrics
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