Towards Computational Models of the Visual Aesthetic Appeal of Consumer Videos
Abstract
In this paper, we tackle the problem of characterizing the aesthetic appeal of consumer videos and automatically classifying them into high or low aesthetic appeal. First, we conduct a controlled user study to collect ratings on the aesthetic value of 160 consumer videos. Next, we propose and evaluate a set of low level features that are combined in a hierarchical way in order to model the aesthetic appeal of consumer videos. After selecting the 7 most discriminative features, we successfully classify aesthetically appealing vs. aesthetically unappealing videos with a 73% classification accuracy using a support vector machine.
Cite
Text
Moorthy et al. "Towards Computational Models of the Visual Aesthetic Appeal of Consumer Videos." European Conference on Computer Vision, 2010. doi:10.1007/978-3-642-15555-0_1Markdown
[Moorthy et al. "Towards Computational Models of the Visual Aesthetic Appeal of Consumer Videos." European Conference on Computer Vision, 2010.](https://mlanthology.org/eccv/2010/moorthy2010eccv-computational/) doi:10.1007/978-3-642-15555-0_1BibTeX
@inproceedings{moorthy2010eccv-computational,
title = {{Towards Computational Models of the Visual Aesthetic Appeal of Consumer Videos}},
author = {Moorthy, Anush K. and Obrador, Pere and Oliver, Nuria},
booktitle = {European Conference on Computer Vision},
year = {2010},
pages = {1-14},
doi = {10.1007/978-3-642-15555-0_1},
url = {https://mlanthology.org/eccv/2010/moorthy2010eccv-computational/}
}