aiqbench analysis
UltraArUco advances mobile augmented reality by introducing a lightweight, multilingual framework that significantly reduces tracking latency compared to standard OpenCV implementations. By optimizing marker-based detection and enabling distributed Wi-Fi architectures, the system facilitates responsive AR interactions on resource-constrained devices without requiring specialized hardware. This development is particularly relevant for real-time computer vision applications in HCI scenarios such as gesture recognition and interactive simulations.
UltraArUco: A Lightweight Multilingual Library And Framework With Low-Latency Real-Time Marker-Based Tracking System For Mobile AR Interaction
arXiv:2608.13584v1 Announce Type: cross Abstract: UltraArUco - a lightweight multilingual library and framework for low-latency, real-time marker-based tracking in mobile augmented reality. Unlike standard OpenCV-based implementations, UltraArUco introduces an optimized multilingual wrapper that reduces per-frame latency by five times, while maintaining high accuracy. Distributed Wi-Fi architecture provides portability, connects a mobile device (camera input) with a PC-based visual application, enabling responsive interactions. The framework is validated through an interactive piano simulation, where static ArUco markers on keys enable occlusion-based note triggering, and hand-mounted markers provide spatial gesture recognition. UltraArUco's system requirements make it perfect for resource-constrained mobile AR applications, demonstrating a viable AR music application without specialized equipment.
Abstract:UltraArUco - a lightweight multilingual library and framework for low-latency, real-time marker-based tracking in mobile augmented reality. Unlike standard OpenCV-based implementations, UltraArUco introduces an optimized multilingual wrapper that reduces per-frame latency by five times, while maintaining high accuracy. Distributed Wi-Fi architecture provides portability, connects a mobile device (camera input) with a PC-based visual application, enabling responsive interactions. The framework is validated through an interactive piano simulation, where static ArUco markers on keys enable occlusion-based note triggering, and hand-mounted markers provide spatial gesture recognition. UltraArUco's system requirements make it perfect for resource-constrained mobile AR applications, demonstrating a viable AR music application without specialized equipment.
Human-Computer Interaction (cs.HC); Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV)
arXiv:2608.13584 [cs.HC]
(or arXiv:2608.13584v1 [cs.HC] for this version)
https://doi.org/10.48550/arXiv.2608.13584 Focus to learn more arXiv-issued DOI via DataCite
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