State-of-the-art in 360{\deg} Video/Image Processing: Perception, Assessment and Compression

TL;DR

This paper reviews recent advances in 360-degree video/image processing, focusing on perception, quality assessment, and compression techniques to address data size challenges.

Contribution

It provides a comprehensive survey of datasets, visual attention models, quality assessment methods, and compression approaches specific to 360-degree media.

Findings

Summarizes datasets and visual attention modeling for 360-degree media

Reviews subjective and objective quality assessment methods

Overviews compression techniques utilizing spherical features and attention models

Abstract

Nowadays, 360{\deg} video/image has been increasingly popular and drawn great attention. The spherical viewing range of 360{\deg} video/image accounts for huge data, which pose the challenges to 360{\deg} video/image processing in solving the bottleneck of storage, transmission, etc. Accordingly, the recent years have witnessed the explosive emergence of works on 360{\deg} video/image processing. In this paper, we review the state-of-the-art works on 360{\deg} video/image processing from the aspects of perception, assessment and compression. First, this paper reviews both datasets and visual attention modelling approaches for 360{\deg} video/image. Second, we survey the related works on both subjective and objective visual quality assessment (VQA) of 360{\deg} video/image. Third, we overview the compression approaches for 360{\deg} video/image, which either utilize the spherical characteristics or visual attention models. Finally, we summarize this overview paper and outlook the future research trends on 360{\deg} video/image processing.