Multiview Navigation based on Extended Layered Depth Image Representation

TL;DR

This paper introduces an extended layered depth image (LDI) method for multiview navigation that improves scene representation efficiency, reducing redundancy and enhancing rate-distortion performance in interactive multiview streaming.

Contribution

It proposes an extended LDI representation for navigation segments, adapting scene size to improve multiview compression in navigation scenarios.

Findings

Significant rate-distortion gain over classical approaches

Enhanced scene representation with extended LDI

Improved efficiency in multiview navigation streaming

Abstract

Emerging applications in multiview streaming look for providing interactive navigation services to video players. The user can ask for information from any viewpoint with a minimum transmission delay. The purpose is to provide user with as much information as possible with least number of redundancies. The recent concept of navigation segment representation consists of regrouping a given number of viewpoints in one signal and transmitting them to the users according to their navigation path. The question of the best description strategy of these navigation segments is however still open. In this paper, we propose to represent and code navigation segments by a method that extends the recent layered depth image (LDI) format. It consists of describing the scene from a viewpoint with multiple images organized in layers corresponding to the different levels of occluded objects. The notion of extended LDI comes from the fact that the size of this image is adapted to take into account the sides of the scene also, in contrary to classical LDI. The obtained results show a significant rate-distortion gain compared to classical multiview compression approaches in navigation scenario.