Publications
Authors:
  • Luca Marchesotti , Florent Perronnin , Diane Larlus , Gabriela Csurka , Loïc Michallon
Citation:
Conférence Reconnaissance des Formes et Intelligence Artificielle, Lyon, France, January 24-27, 2012.
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.
Year:
2012
Report number:
2011/051