Visual quality assessment of reconstructed background images

Abstract

A clean background image is of great importance in multiple applications such as video surveillance, object tracking and context-based video encoding, but acquiring a clean background image in public areas is seldom possible. Many algorithms have been developed to initialize the background from videos and images. This paper presents a database consisting of 13 different scenes that can be used for benchmarking the performance of background initialization algorithms. We also conducted a subjective study on the perceptual quality of background images that are reconstructed using existing background initialization algorithms. The obtained subjective scores are used to evaluate existing image quality metrics and their capability in predicting the perceived quality of reconstructed background images.