Content for TR 26.998 Word version: 18.0.0

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A.4 Use Case 19: AR Conferencing
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A.4 Use Case 19: AR Conferencing p. 113

Use Case Description: AR Conferencing
This clause describes an AR conferencing use-case that allows participants in a 3D volumetric representation, e.g. point clouds or meshes, in order to provide an immersive conferencing experience. AR Conferencing (1:1) Bob and Alice want to make an AR conferencing call. Both are wearing AR glasses. Bob is located in Stockholm while Alice is located in Aachen. One or more cameras are placed in each location and are filming Bob and Alice, respectively. Bob can see a 3D volumetric representation of Alice on his AR headset and Alice can see a 3D volumetric representation of Bob on her AR headset. Bob and Alice can enjoy a truly immersive audio-visual experience. Figure A.4-1: AR Conferencing (1:1) (⇒ copy of original 3GPP image) AR Conferencing (1:many) Bob and Alice are invited to an escalation meeting. Bob is able to physically attend the meeting, whereas Alice is virtually joining the meeting. Alice can be seen by Bob and other participants as a 3D volumetric representation on their AR glasses. Bob and other participants can interact with the 3D volumetric representations (e.g. rotate, zoom-in, resize). Alice can see and interact with Bob and other participants. Alice may use a laptop, phone, AR or VR device to visualize participants in the office. All participants can enjoy a truly immersive audio-visual experience. Figure A.4-2: AR Conferencing (1:many) (⇒ copy of original 3GPP image)
Categorization
Type: AR Degrees of Freedom: 3DoF+ or 6DoF Delivery: Conversational Device: AR glasses
Preconditions
The participants are located in a room that is equipped with cameras that allow the capturing of participants including depth information. The movements can be captured by other means (e.g. AR glasses or phone camera). The participants are wearing AR glasses that allow the 3D volumetric representation of other participants.
Requirements and QoS/QoE Considerations
The network is required support the delivery of 3D volumetric streams for real-time conversational services: Support of different volumetric user representation formats. bitrates and latencies that are sufficient to stream volumetric user representations under conversational real-time constrains.
Feasibility
The bandwidth and latency requirements for AR conferencing using 3D volumetric representations present a challenge to mobile networks. The complexity of the 3D volumetric representations is challenging for the endpoints and introduces additional delay for processing and rendering functions. Intermediate edge or cloud components are needed. In the following some indicative values of potential solution and transmission format for different types of user representation: A point cloud stream has raw bandwidth requirement of up to 2 Gbps. The transmission bandwidth is expected to be lower after encoding and optimization. Preliminary data from MPEG V-PCC codec evaluation indicates compression ratios "in the range of 100:1 to 300:1" [40]. For dynamic sequences of 1M points per frame this could result into an encoding bitrate of "8 Mbps with good perceptual quality" [40]. For conversational services, we expect lower compression ratios. 2D/RGB+Depth: >2.7Mbps (1 camera @ 30fps with total resolution of 1080x960 [37]), >5.4Mbps (2 Camera @ 30fps with total resolution of 1080x1, 92 [38]). 3D Mesh: ~30 Mbps @ 20-25 FPS (with a voxel grid resolution of 64x128x64 and 12-15k vertices) [39]. Preliminary data from 3D GPCC show that bitrates in the range of 5-50 Mbps @ 30 fps with varying octree depth and varying JPEG QP are expected [39].
Potential Standardization Status and Needs
The following aspects may require standardization work: Standardized formats for 3D volumetric representation of participants on AR glasses. Cloud APIs for processing and rendering of 3D volumetric streams. Conversational methods for call initiation. Spatial audio formats and associated metadata. Metadata for Spatial characteristics of the AR environment (e.g. positioning of users).