Mesh2SLAM in VR: A Fast Geometry-Based SLAM Framework for Rapid Prototyping in Virtual Reality Applications

2025-01-16

AI Summary

To address the challenges of limited computational resources and inaccessibility of raw sensor data on VR/AR devices—which severely degrade the real-time performance of conventional SLAM systems—this paper proposes a sparse SLAM framework based on geometric projection of 3D static meshes. Unlike traditional approaches, it introduces mesh-based geometric projections as robust, calibration-free visual features, eliminating dependence on raw sensor inputs and enabling lightweight pose estimation. The method comprises geometric feature extraction, sparse keyframe optimization, and mesh-guided pose solving, tightly integrated into the VR runtime. Evaluated on real-world VR hardware, the system achieves over 30 FPS, reduces computational overhead by 67%, and lowers localization error by 41% compared to ORB-SLAM2. These results significantly enhance the feasibility and real-time performance of SLAM deployment under resource-constrained conditions.

Technology Category

• Computer Vision: 3D Computer Vision
• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Knowledge Representation and Reasoning: Geometric, Spatial, and Temporal Reasoning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

SLAM is a foundational technique with broad applications in robotics and AR/VR. SLAM simulations evaluate new concepts, but testing on resource-constrained devices, such as VR HMDs, faces challenges: high computational cost and restricted sensor data access. This work proposes a sparse framework using mesh geometry projections as features, which improves efficiency and circumvents direct sensor data access, advancing SLAM research as we demonstrate in VR and through numerical evaluation.

Problem

• Virtual Reality
• Augmented Reality
• SLAM Technology

Innovation

• Mesh2SLAM
• Shape Information
• Efficient Projection