4 citations · 8 across the 5 of their papers we have counts for
6 papers
SIGNN++: Robust Graph Neural Star Identification on Earth
Jeongbin Sohn, Jina Lee, Max Yen +6
We present SIGNN++, a learning-based star identification (SID) framework for celestial navigation in GNSS-denied nighttime environments. Although researchers have developed learnin…
GALoc: Gravity Aligned Wireframes for Depth-Free Monocular Floorplan Localization
Jeahn Han, Minji Kim, Jeongbin Sohn +3
Floorplans are compact, appearance-invariant maps ideal for indoor localization, yet existing methods rely on depth networks that are brittle in cluttered scenes. We propose GALoc,…
SoMaSLAM: 2D Graph SLAM for Sparse Range Sensing with Soft Manhattan World Constraints
Jeahn Han, Zichao Hu, Seonmo Yang +2
We propose a graph SLAM algorithm for sparse range sensing that incorporates a soft Manhattan world utilizing landmark-landmark constraints. Sparse range sensing is necessary for t…
An Empirical Evaluation of Four Off-the-Shelf Proprietary Visual-Inertial Odometry Systems
Jungha Kim, Minkyeong Song, Yeoeun Lee +2
Commercial visual-inertial odometry (VIO) systems have been gaining attention as cost-effective, off-the-shelf six degrees of freedom (6-DoF) ego-motion tracking methods for estima…
Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments
Sachini Herath, Saghar Irandoust, Bowen Chen +3
The paper proposes a multi-modal sensor fusion algorithm that fuses WiFi, IMU, and floorplan information to infer an accurate and dense location history in indoor environments. The…
Moving object detection for visual odometry in a dynamic environment based on occlusion accumulation
Haram Kim, Pyojin Kim, H. Jin Kim
Detection of moving objects is an essential capability in dealing with dynamic environments. Most moving object detection algorithms have been designed for color images without dep…