A Motion-Simulation Platform to Generate Synthetic Motion Data for Computer Vision Tasks

Andrew Chalmers, Junhong Zhao, Weng Khuan Hoh, James Drown, Simon Finnie, Richard Yao, James Lin, James Wilmott, Arindam Dey, Mark Billinghurst, Taehyun Rhee

Abstract: We developed the Motion-Simulation Platform, a platform running within a game engine that is able to extract both RGB imagery and the corresponding intrinsic motion data (i.e., motion field). This is useful for motion-related computer vision tasks where large amounts of intrinsic motion data are required to train a model. We describe the implementation and design details of the Motion-Simulation Platform. The platform is extendable, such that any scene developed within the game engine is able to take advantage of the motion data extraction tools. We also provide both user and AI-bot controlled navigation, enabling user-driven input and mass automation of motion data collection.