Authors: Thomas Maugey, Olivier Le Meur, Zhi Liu
Title: Saliency-based navigation in omnidirectional image, submitted to IEEE MMSP 2017
Abstract: Omnidirectional images describe the color information at a given position from all directions. Affordable 360° cameras have recently been developed leading to an explosion of the 360° data shared on the social networks. However, an omnidirectional image does not contain interesting content everywhere. Some part of the images are indeed more likely to be looked at by some users than others. Knowing these regions of interest might be useful for 360° image compression, streaming, retargeting or even editing. In this paper, a new approach based on 2D image saliency is proposed both to model the user navigation within a 360° image, and to detect which parts of an omnidirectional content might draw users’ attention.