Saliency-Based Sharpness Mismatch Detection For Stereoscopic Omnidirectional Images

Abstract

In this paper, we present a novel sharpness mismatch detection (SMD) approach for stereoscopic omnidirectional images (ODI) for quality control within the post-production workflow, which is the main contribution. In particular, we applied a state of the art SMD approach, which was originally developed for traditional HD images, and extended it to stereoscopic ODIs. A new efficient method for patch extraction from ODIs was developed based on the spherical Voronoi diagram of evenly distributed points on the sphere. The subdivision of the ODI into patches allows an accurate detection and localization of regions with sharpness mismatch. A second contribution of the paper is the integration of saliency into our SMD approach. In this context, we introduce a novel method for the estimation of saliency maps from viewport data of head-mounted displays (HMD). Finally, we demonstrate the performance of our SMD approach with data collected from a subjective test with 17 participants.