RealTime Streaming of Sequential Volumetric Data for Augmented Reality Synchronized with Broadcast Video Commercial 4K8K satellite broadcasting began in Japan in December 2018. It has been said that 8K video will be the ultimate twodimensional (2D) video medium, and one of next challenges for future digital media technologies will be to deliver threedimensional (3D) information. Augmented reality (AR) is attracting increasing attention, but its expressiveness and visual quality are still limited. We have previously proposed a new viewing style where viewers watch 2D video on a television while simultaneously experiencing 3D AR content on a seconddisplay device. In this paper, we describe a system for realtime streaming of sequential volumetric data to provide AR content on seconddisplay devices. To synchronize the video and AR presentations, we utilize the coordinateduniversaltimebased presentation timestamps provided by MPEG media transport (MMT), which is the internetprotocolbased media transport scheme adopted for the 4K8K broadcasting. We evaluate our systemxe2x80x99s interdevice synchronization function by transmitting volumetric data and video, captured simultaneously in a volumetric capture studio.

Dynamic Adaptive Streaming for Augmented Reality Applications Augmented Reality (AR) superimposes digital content on top of the real world, to enhance it and provide a new generation of media experiences. To provide a realistic AR experience, objects in the scene should be delivered with both high photorealism and low latency. Current AR experiences are mostly delivered with a downloadandplay strategy, where the whole scene is considered a monolithic entity for delivery. This approach results in high startup latencies and therefore a poor user experience. A similar problem in the video domain has already been tackled with the HTTP Adaptive Streaming (HAS) principle, where the video is split into segments, and a rate adaptation heuristic dynamically adapts the video quality based on the available network resources. In this paper, we apply the adaptive streaming principle from the video to the AR domain, and propose a streaming framework for AR applications. In our proposed framework, the AR objects are available at different LevelsOfDetail (LODs) and can be streamed independently from each other. An LOD adaptation heuristic is in charge of dynamically deciding what object should be fetched from the server and at what LOD level. Our proposed heuristic prioritizes content that is more likely to be viewed by the user and selects the best LOD to maximize the objectu0027s perceived visual quality. Moreover, the adaptation takes into account the available bandwidth resources to ensure a timely delivery of the AR objects. Experiments carried out over the Internet using an AR streaming prototype developed on an iOS device allow us to show the gains brought by the proposed framework. Particularly, our approach can decrease startup latency up to 90% with respect to a downloadandplay baseline, and decrease the amount of data needed to deliver the AR experience up to 79%, without sacrificing on the visual quality of the AR objects.