The Design of High-Level Features for Photo Quality Assessment

1 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.

• Type: Conference
• Year: 2006
• Where: CVPR
• Authors: Yan Ke, Xiaoou Tang, Feng Jing
• Keywords: Computer Vision, CVPR 2006, Level Semantic Features, Low Quality Snapshots, Low Recall Scenarios, Photo Quality Assessment, Quality Professional Photos