CHINGMU and AMD rewrite the world record: 100-person simultaneous real-time motion capture
Published June 1, 2026
Shanghai - CHINGMU hosted its â100 People Enter the Digital World Simultaneouslyâ real-time motion capture challenge & digital motion showcase at the CHINGMU MCP Boundless Studio in Shanghai. AMD served as the lead computing partner. The event featured a live performance by 100 motion-capture actors, demonstrating the synergy of large-scale optical motion capture, AI computing, real-time digital character animation, and embodied AI.
The entire challenge was witnessed and officially documented on-site by the Shanghai New Hongqiao Notary Public Office, which issued a notarial certificate attesting to the authenticity of all generated technical data.
The First Publicly Verified 100-Person Real-Time Motion Capture System
The system used 76 CHINGMU Kunpeng (K) Series K26 optical motion capture cameras, together with a single high-performance workstation equipped with a 64-core AMD Ryzen Threadripper PRO 9985WX processor and an AMD Radeon RX 9070 XT graphics card (16GB VRAM). Operating at an industrial-grade 120 fps, it captured approximately 5,300 markers across 100 actors, while performing real-time 3D reconstruction, marker identification, and skeletal solving with an end-to-end latency under 12 ms.
According to publicly available sources, the previous internationally certified record for real-time multi-person motion capture stood at 19 persons, while the highest publicly demonstrated scale in China was approximately 41 persons. This challenge pushed the scale to 100 persons for the first time-a 2.3-fold increase in participant count and an exponential leap in data volume-making it the largest publicly verified real-time multi-person motion capture achievement on record, and marking a new era of industrial-scale 100-person applications for global motion capture technology.
From Dozens to 100: The System-Level Challenges
Scaling real-time motion capture from dozens to 100 people is not a linear superposition of technologies, but a comprehensive test of multi-target recognition, occlusion handling, real-time solving, system synchronizationï¼ and long-term stable operation.
Exponential Data Volume Explosion: The system processed roughly 60,000 2D image points from 76 cameras per frame, equating to 7.2 million 2D image points per second-all within an 8 ms single-frame window, while maintaining an end-to-end latency below 12 ms.
Occlusion and Identity Recognition: With 100 performers moving simultaneously, marker loss and re-acquisition, mis-assignment, and skeletal drift increase exponentially, and error correction must compete for computing resources within the real-time window.
Stable End-to-End Operation: All 100 motion data streams must remain strictly synchronized, and the system had to run under heavy load continuously for over one hour without crashes, frame drops, or memory leaks.
Coupled with the high organizational cost and limited trial-and-error space for a 100-person team, these interconnected challenges have made 100-person real-time motion capture a recognized technical "no man's land" in the industry.
System Synergy: Deep Integration of CHINGMU and AMD
The success of this challenge is the result of the collaborative operation of optical motion capture systems, real-time algorithms, on-site engineering deployment, and high-performance computing platforms. CHINGMU was responsible for the overall design of the motion capture system and core algorithm R&D, while AMD provided computing power support for high-concurrency data processing and real-time visualization.
CHINGMU redesigned core algorithms for 100-person high-concurrency scenarios, improving key algorithmic efficiency by over 300% and optimizing marker recognition strategies to solve occlusion and misalignment problems. AMD's high-performance CPU and GPU undertake high-concurrency thread scheduling, motion solving and real-time rendering tasks respectively. Through joint optimization of BIOS configuration, thread scheduling and data paths by both teams, the overall system performance was further improved by 20%, achieving stable millisecond-level operation in 100-person motion capture scenarios.
From Technology Breakthrough to Industry Enablement
The core value of this challenge goes beyond breaking the world record. It fully verifies the engineering capability of motion capture systems for large-space, high-concurrency, and complex interaction scenarios, opening new application boundaries for the digital economy and embodied intelligence industries. This capability can deeply empower digital content production fields such as group animation, virtual production and digital performance, while enabling applications including robot teleoperation, humanoid robot motion learning, and embodied intelligence dataset construction, providing key data support for intelligent systems to understand real-world movements.
This is not only a technological milestone but also a validation of CHINGMU's ability to build large-scale real-time motion data infrastructure for the entire industry. The 100-person scale is by no means the end. As the capture space, camera arrays, and computing platforms continue to evolve, real-time multi-person motion capture has vast potential to scale even further. Moving forward, CHINGMU will continue to advance high-precision motion capture and multi-modal data acquisition, building a high-precision motion data infrastructure that connects the physical world, the digital world, and the robotics industry, and driving the development of the global digital intelligence industry.
Company: SHANGHAI CHINGMU VISION TECHNOLOGY CO., LTD
Contact Person: Violet
Email: lienrui@chingmu.com
Website: https://en.chingmu.com/
Telephone: 13310099680
