by Yan Ke,
Xiaoou Tang, and
Feng Jing
Abstract:
We propose a principled method for designing high
level features for photo quality assessment. Our resulting
system can classify between high quality professional photos
and low quality snapshots. Instead of using the bag
of low-level features approach, we first determine the perceptual
factors that distinguish between professional photos
and snapshots. Then, we design high level semantic features
to measure the perceptual differences. We test our features
on a large and diverse dataset and our system is able to
achieve a classification rate of 72% on this difficult task.
Since our system is able to achieve a precision of over 90%
in low recall scenarios, we show excellent results in a web
image search application.
A talk based on this work: Taking Great Pictures (Automatically). Guest lecture for Computational Photography. Nov 27, 2007.
Y. Ke, X. Tang, and F. Jing. In Proceedings of Computer Vision and
Pattern Recognition,
2006. [PDF 800KB]
| Images used in ranking | Ranked results (rank in filename) |
| Apple | Apple Results |
| Statue of Liberty | Statue of Liberty Results |
| Cow | Cow Results |
| BMW | BMW Results |
| Rose | Rose Results |
| Violin | Violin Results |
Commentary on the above results.
March 2006