AR Mapping: Accurate and Efficient Mapping for Augmented Reality
Rui Huang, Chuan Fang, Kejie Qiu, Le Cui, Zilong Dong, Siyu Zhu, Ping, Tan

TL;DR
This paper introduces a comprehensive end-to-end method for creating accurate and efficient AR maps, including data capture, mapping, and evaluation, to enhance localization in augmented reality systems.
Contribution
It presents the first complete pipeline for AR mapping that integrates data collection, map generation, and accuracy assessment, improving localization accuracy in AR applications.
Findings
Developed a backpack scanning device with a unified calibration pipeline.
Proposed an end-to-end AR mapping pipeline from data capture to map generation.
Validated AR map accuracy using high-end laser scanner reconstructions.
Abstract
Augmented reality (AR) has gained increasingly attention from both research and industry communities. By overlaying digital information and content onto the physical world, AR enables users to experience the world in a more informative and efficient manner. As a major building block for AR systems, localization aims at determining the device's pose from a pre-built "map" consisting of visual and depth information in a known environment. While the localization problem has been widely studied in the literature, the "map" for AR systems is rarely discussed. In this paper, we introduce the AR Map for a specific scene to be composed of 1) color images with 6-DOF poses; 2) dense depth maps for each image and 3) a complete point cloud map. We then propose an efficient end-to-end solution to generating and evaluating AR Maps. Firstly, for efficient data capture, a backpack scanning device is…
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Taxonomy
TopicsRobotics and Sensor-Based Localization · Augmented Reality Applications · Advanced Image and Video Retrieval Techniques
