Google is accelerating the commercialization of its AI-based 3D remote conferencing solution, "Google Beam," as a domestic parts supplier successfully entered its supply chain. If the next-generation telepresence technology, which allows users to see others as if they are physically present without the need for glasses or headsets, becomes widely adopted, demand for sensors, cameras, and optical components is expected to rise significantly.
According to a report by Aju Economy on June 9, Namuga, a domestic sensor specialist and partner of Samsung Electronics, has completed the proof of concept (PoC) for the Google Beam supply chain and will begin delivering related components by the end of this year. An industry insider stated, "The vendor selection has been completed, and contracts have been finalized."
Google Beam is an AI-driven video conferencing platform developed by Google. Unlike traditional video conferencing, which displays participants in flat images, Google Beam utilizes multiple cameras and sensors to recognize users' faces and movements in real-time, reconstructing them into 3D video. This technology enables natural gaze handling and depth perception, making it feel as though participants are in the same space without the need for additional glasses or headsets.
Google announced the video communication tool Google Beam at its annual developer conference last year. At this year's CES, the company showcased related technology, marking its serious entry into the corporate market. Analysts suggest that the market could expand beyond video conferencing into healthcare and education sectors.
Google Beam requires high-precision 3D sensors and image sensors to collect spatial information in real-time, including users' facial contours, distances, and movements. The sensors are essential for implementing volumetric video modeling, a core technology of Google Beam. This technology involves AI analyzing video data collected from multiple cameras at various angles to reconstruct real-time 3D video. Accurate collection of users' facial shapes, movements, and distance information is crucial for generating natural 3D visuals.
Additionally, the technology will apply monocular depth estimation, which estimates spatial information using a single camera. AI calculates the distance and depth of people and objects in the video to create a realistic spatial experience. This process also requires high-performance sensors to accurately capture facial contours, positions, and movement data.
The market outlook is promising. According to market research firm VirtuMarket Research, the global 3D telepresence market is projected to grow from $1.78 billion in 2024 to $6.2 billion by 2030, with an average annual growth rate of 19.5%. The expansion of generative AI and related technologies is expected to drive this market growth.
A Namuga representative stated, "While we cannot confirm specifics, we are currently in discussions with global companies regarding supply."
* This article has been translated by AI.
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