Augmented Reality without Borders: Achieving Precise Localization Without Maps

TL;DR

MARLoc is a new AR localization method that achieves precise outdoor positioning without pre-built maps by using intra-sequence triangulation, enabling efficient and robust real-world AR applications.

Contribution

Introduces MARLoc, a mapless visual localization framework that uses relative transformations and intra-sequence triangulation for accurate pose estimation in outdoor AR.

Findings

State-of-the-art localization accuracy demonstrated on benchmark datasets.

Robust performance in dynamic outdoor environments.

Efficient localization without pre-built 3D maps.

Abstract

Visual localization is crucial for Computer Vision and Augmented Reality (AR) applications, where determining the camera or device's position and orientation is essential to accurately interact with the physical environment. Traditional methods rely on detailed 3D maps constructed using Structure from Motion (SfM) or Simultaneous Localization and Mapping (SLAM), which is computationally expensive and impractical for dynamic or large-scale environments. We introduce MARLoc, a novel localization framework for AR applications that uses known relative transformations within image sequences to perform intra-sequence triangulation, generating 3D-2D correspondences for pose estimation and refinement. MARLoc eliminates the need for pre-built SfM maps, providing accurate and efficient localization suitable for dynamic outdoor environments. Evaluation with benchmark datasets and real-world experiments demonstrates MARLoc's state-of-the-art performance and robustness. By integrating MARLoc into an AR device, we highlight its capability to achieve precise localization in real-world outdoor scenarios, showcasing its practical effectiveness and potential to enhance visual localization in AR applications.