Abstract:
This paper presents an automatic personalized photo recommender system which recommends
photos from a large collection. Our proposed system recommends photos based on userpreferences
about aesthetics and visual quality features of the photo. A large dataset has been put
together, which has been used to collect user-preferences. A random forest based learning system
has been invoked to learn the user preferences about different image features including aesthetic
features. The system is validated using a part of the collected user preferences as ground truth and
it has been compared to a random selection of photographs. Our automatic system significantly
outperforms the random selection, which shows the usefulness of our proposal, especially when
the collection of photos is manually unmanageable.
