It is typically challenging for visual or visual-inertial odometry systems to handle the
problems of dynamic scenes and pure rotation. In this work, we design a novel visual-inertial …

In this paper, we propose a tightly-coupled SLAM system fused with RGB, Depth, IMU and
structured plane information. Traditional sparse points based SLAM systems always …

Feature matching is crucial in visual localization, where 2D-3D correspondence plays a
major role in determining the accuracy of camera pose. A sufficient number of well …

Markerless motion capture (Mocap) has the capability to provide precise positioning, and the
integration of Mocap with the inertial measurement unit (IMU) holds significant promise for …

Globally-consistent localization in urban environments is crucial for autonomous systems
such as self-driving vehicles and drones, as well as assistive technologies for visually …

The accurate extraction of feature points has a significant impact on the pose estimation of
visual SLAM system, in weak textured environments such as underground parking lots …

Achieving precise real-time localization and ensuring robustness are critical challenges in
multi-user mobile AR applications. Leveraging collaborative information to augment tracking …

The paper studies the real-time stereo image-based localization of a vehicle in a prior 3D
LiDAR map. A novel localization approach for mobile ground robot, which successfully …

This paper presents a novel approach to Visual Inertial Odometry (VIO), focusing on the
initialization and feature matching modules. Existing methods for initialization often suffer …

State-of-the-art hierarchical localisation pipelines (HLoc) employ image retrieval (IR) to
establish 2D-3D correspondences by selecting the top-$ k $ most similar images from a …