iMarker: Instant and True-to-scale AR with Invisible Markers
Chang Xiao, Ryan A. Rossi, Eunyee Koh · 2022
Augmented Reality (AR) has been widely used in modern mobile devices for various applications. To achieve a stable and precise AR experience, mobile devices are equipped with various sensors (e.g., dual camera, LiDAR) to increase the robustness of camera tracking. Those sensors largely increased the cost of mobile devices and are usually not available on low-cost devices. We propose a novel AR system that leverage the advance of marker-based camera tracking to produce fast and true-to-scale AR rendering on any device with a single camera. Our method enables the computer monitor to be the host of AR markers, without taking up valuable screen space nor impacting the user experience. Unlike traditional marker-based methods, we utilize the difference between human vision and camera system, making AR markers to be invisible to human vision. We propose an efficient algorithm that allows the mobile device to detect those markers accurately and later recover the camera pose for AR rendering. Since the markers are invisible to human vision, we can embed them on any website and the user will not notice the existence of these markers. We also conduct extensive experiments that evaluate the efficacy of our method. The experimental results show that our method is faster and has a more accurate scale of the virtual objects compared to the state-of-the-art AR solution.