PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Assessing the aesthetic quality of photographs using generic image descriptors
Luca Marchesotti, Florent Perronnin, Diane Larlus and Gabriela Csurka
International Conference on Computer Vision pp. 1784-1791, 2011.

Abstract

In this paper, we automatically assess the aesthetic properties of images. In the past, this problem has been addressed by hand-crafting features which would correlate with best photographic practices (e.g. “Does this image respect the rule of thirds?”) or with photographic techniques (e.g. “Is this image a macro?”). We depart from this line of research and propose to use generic image descriptors to assess aesthetic quality. We experimentally show that the descriptors we use, which aggregate statistics computed from low-level local features, implicitly encode the aesthetic properties explicitly used by state-of-the-art methods and outperform them by a significant margin.

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:8953
Deposited By:Diane Larlus
Deposited On:21 February 2012