The CERTH-ITI-VAQ700 dataset
Our aim is to provide a comprehensive video dataset for the problem of aesthetic quality assessment consisting of user-created videos capturing moments of everyday life, such as excursions, school concerts, and training processes. We downloaded from YouTube 700 videos covering a variety of categories, such as outdoor activities, do it yourself videos, make up tutorials, lectures, and home-made videos, licensed under Creative Commons Attribution. The duration of each of these videos ranges from 1 to 6 minutes.
We conducted an annotation process that involved 12 annotators watching and evaluating the aesthetic value of these videos by assigning binary aesthetic quality ratings; 1 being assigned to videos of high aesthetic quality and 0 to videos of low aesthetic quality. Each video was assessed by 5 annotators. The final aesthetic score of each annotated video was calculated as the median score of the annotators' individual scores. As a result of the annotation process, 350 videos are rated as being of high aesthetic quality and another 350 as being of low aesthetic quality.
A comprehensive representation scheme that exploits photo- and motion-based features, motivated by photography and cinematography rules, is also provided for this dataset. For more details concerning the extracted video features, please refer to .
The CERTH-ITI-VAQ700 dataset includes:
700 YouTube videos in .mp4 format (download here)
Video features (download here)
Annotation (download here)
All videos were downloaded from YouTube, where they were available under the Creative Commons License. This means that the dataset is available for research, non-commersial purposes. For more details on data use and re-use please refer to CC BY license.
If you use the CERTH-ITI-VAQ700 dataset in your research work, please cite the following paper:
 C. Tzelepis, E. Mavridaki, V. Mezaris, I. Patras "Video Aesthetic Quality Assessment using Kernel Support Vector Machine with Isotropic Gaussian Sample Uncertainty (KSVM-iGSU)", Proc. IEEE International Conference on Image Processing (ICIP 2016), Phoenix, Arizona, USA, September 2016