Predicting Media Interestingness Dataset
This dataset is intended to be used for assessing the quality of methods for automatic prediction of interestingness of images and videos. It contains interestingness annotations for 103 movie trailers and 4 continuous extracts of ca. 15min from full-length movies.
The dataset was validated during the 2017 Predicting Media Interestingness Task at the MediaEval Benchmarking Initiative for Multimedia Evaluation.
For more details see:
- C.-H. Demarty, M. Sjöberg, B. Ionescu, T.-T. Do, M. Gygli, N.Q.K. Duong, “MediaEval 2017 Predicting Media Interestingness Task”, MediaEval Benchmarking Initiative for Multimedia Evaluation, vol. 1984, CEUR-WS.org, ISSN: 1613-0073, 2017 (task overview paper describing the dataset and the task - download PDF).
We would like to thank Yu-Gang Jiang and Baohan Xu from the Fudan University, China, Hervé Bredin, from LIMSI, France, and Michael Gygli for providing the features that accompany the released data.
This dataset was made possible by the collaboration of the following projects: UEFISCDI research grant PN-III-P2-2.1-PED-2016-1065, agreement 30PED/2017, project SPOTTER.