Year: 2023
Type: conference-paper
Abstract: Mobile augmented reality (AR) has a wide range of promising applications, but its efficacy is subject to the impact of environment texture on both machine and human perception. Performance of the machine perception algorithm underlying accurate positioning of virtual content, visual-inertial SLAM (VI-SLAM), is known to degrade in low-texture conditions, but there is a lack of data in realistic scenarios. We address this through extensive experiments using a game engine-based emulator, with 112 textures and over 5000 trials. Conversely, human task performance and response times in AR have been shown to increase in environments perceived as textured. We investigate and provide encouraging evidence for invisible textures, which result in good VI-SLAM performance with minimal impact on human perception of virtual content. This arises from fundamental differences between VI-SLAM-based machine perception, and human perception as described by the contrast sensitivity function. Our insights open up exciting possibilities for deploying ambient IoT devices that display invisible textures, as part of systems which automatically optimize AR environments.
Institution: Duke University
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Awards: CAREER: Foundations of IoT-Supported Mobile Augmented Reality, CNS Core: Small: Collaborative Research: Towards Intelligent Multi-User Augmented Reality with Edge Computing, G6671297155, CSR: Small: Collaborative Research: Multi-tier Service Architecture in IoT-Edge-Cloud-Paradigms, AI Institute for Edge Computing Leveraging Next Generation Networks (Athena)
OpenAlex ID: W4386636615