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 78 Hollywood movie trailers.
The dataset was validated during the 2016 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, H. Wang, N.Q.K. Duong, F. Lefebvre, "Predicting Media Interestingness Task", MediaEval Benchmarking Initiative for Multimedia Evaluation, vol. 1739, CEUR-WS.org, ISSN: 1613-0073, Hilversum, Netherlands, October 20-21, 2016 (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, and Hervé Bredin, from LIMSI, France for providing the features that accompany the released data, and Alexey Ozerov and Vincent Demoulin for their valuable inputs to the dataset definition.
This dataset was made possible by the collaboration of the following projects: the National Natural Science Foundation of China under Grant 61472281; the "Shu Guang'' project of Shanghai Municipal Education Commission and Shanghai Education Development Foundation under Grant 12SG23; the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning (No. GZ2015005).