Sensation-based Photo Cropping
[Abstract]
This paper proposes a novel method for automatically cropping a photo
using a quality classifier that assesses whether the cropped region is
agreeable to users. We statistically build this quality classifier using
large photo collections available on websites where people manually
insert quality scores to photos. We first trim the original image and
then decide on the candidates for cropping. We find the cropped region
with the highest quality score by applying the quality classifier to the
candidates. Current automatic photo cropping techniques search for
attention grabbing regions that consist of salient pixels from the
original photo. They are not always pleasant to users because they do
not take into account the quality of the cropped region. Our method with
the quality classifier outperforms a state-of-the-art method that takes
into consideration only the user's attention for automatic photo
cropping.
[Publication]
- Masashi Nishiyama, Takahiro Okabe, Yoichi Sato, and Imari Sato,
Sensation-based Photo Cropping,
Proceedings of ACM International Conference on Multimedia (ACM MM), October 2009.
[Publication (Japanese) ]
[Short movies]
