MediaEval 2017 Predicting Media Interestingness Task



MediaEval 2017 Predicting Media Interestingness Task

MediaEval 2017 Predicting Media Interestingness Task
Research Paper / MediaEval 2017 Workshop / Sep 2017 / Machine/Deep Learning/AI, Computer Vision

In this paper, the Predicting Media Interestingness task which is running for the second year as part of the MediaEval 2017 Benchmarking Initiative for Multimedia Evaluation, is presented. For the task, participants are expected to create systems that automatically select images and video segments that are considered to be the most interesting for a common viewer. All task characteristics are described, namely the task use case and challenges, the released data set and ground truth, the required participant runs and the evaluation metrics.

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