Revolutionizing Motion Capture: Move's AI Technology Redefines the Industry

The concept of motion capture often conjures up images of actors clad in black spandex suits adorned with rubber balls. However, this norm is on the verge of becoming a relic of the past, thanks to Move's groundbreaking software. This technology has the potential to revolutionize motion capture for both AAA and indie game developers, as well as applications beyond the gaming industry. According to Millar, 'We've developed a platform that enables the capture of authentic, high-quality human motion using standard video cameras.' This platform allows for the capture of extremely high-quality human motion, which can then be seamlessly transferred to various avatars or 3D models and utilized within different game engines to power engaging user content. The technology has been tested with popular game engines like Unreal and Unity, as well as Roblox and proprietary engines. In fact, Move has already partnered with Electronic Arts, which showcased impressive results at the annual SIGGRAPH conference last year in Vancouver. The demonstration highlighted the ability of Move's system to achieve the same level of quality and accuracy as traditional motion capture methods. The significant difference in costs and practicalities is what Millar hopes will make Move an attractive option. Traditionally, capturing high-quality human motion requires actors to wear suits, including children and animals, which can be uncomfortable and restrictive. The process also demands a controlled environment with precise lighting conditions and the use of dozens of high-end specialist cameras. In contrast, Move's technology aims to make motion capture more accessible, allowing for high-quality motion to be captured with as few as two cameras, which can be off-the-shelf products or even iPhones. The idea is that this can be done anywhere, eliminating the need for a studio. Move's software leverages advanced AI, computer vision, biomechanics, and physics to track multiple points on the human body without the need for markers. Millar explains, 'We ensure that everything adheres to the laws of motion and momentum to guarantee accurate and authentic capture.' This technology has the potential to be a game-changer, particularly in the context of the pandemic when studios faced significant challenges adapting to remote capture. The idea for Move was born out of Millar's personal experience after the birth of his son, when he began working out from home using apps. He realized the potential for using technology to track human motion in 3D and created his own digital coach. This eventually evolved into Move, a platform that helps users across various mediums digitize their motions. In the context of motion capture for games, Move represents a paradigm shift, offering a more accessible and cost-effective solution for indie developers. The ability to capture multiple people at once on a limited budget is a significant advantage. Millar envisions a big potential for Move in the metaverse, where users can create avatars that not only look like them but also move like them. 'Motion is like a fingerprint,' he says. 'If you capture someone's motion and see it as a stick figure, you can tell it's them because of how they move.' This ability to capture unique motion from a wide variety of people has significant implications for sports games, where the technology could be used to capture the movements of entire teams or individual athletes like LeBron James. However, this raises questions about consent and the potential for motion to be used without permission. Millar acknowledges the need for a legal framework for motion licensing and rights as the industry recognizes the opportunity. Move's approach is to ensure the highest fidelity motion and work with talent and rights owners to create official licensed products. The company's mission is to make human motion digitization accessible to more people, eliminating the restrictions of current systems. With Move, users can set up motion capture in less than five minutes using just iPhones, making it a more iterative and accessible process.