CMU VASC talk: Photo Quality Assessment: Classifying Between Professional Photos and Amateur Snapshots

Yan Ke, CMU
Monday, Feb 6, 2006

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.

Bio:
Yan Ke is a fourth year graduate student in the CMU Computer Science Department. His interests are in computer vision. He spent four months in Beijing, China. When he was not busy touring China and eating good food, he worked on the photo quality assessment project at Microsoft Research Asia.