1 citations · 2 across the 5 of their papers we have counts for
6 papers
Recovering from Pose-Selection Failures in Repeated Visual Localization
Jaehyun Kim, Wonseok Kang, Tae-Wan Kim
Repetitive structures can give an incorrect pose candidate more inlier support than an accurate one, causing visual localization to select it. History-Guided Pose Reselection (HPR)…
Reference-Induced Consensus for Selective Posed-Reference Visual Localization
Wonseok Kang, Jaehyun Kim, Jeongmin Lee +1
We present RIC-Loc (Reference-Induced Consensus localization), a scene-training-free posed-reference localizer that is SfM-point-map-free in its main estimator: it uses known refer…
Surfel-LIO: Fast LiDAR-Inertial Odometry with Pre-computed Surfels and Hierarchical Z-order Voxel Hashing
Seungwon Choi, Dong-Gyu Park, Seo-Yeon Hwang +1
LiDAR-inertial odometry (LIO) is an active research area, as it enables accurate real-time state estimation in GPS-denied environments. Recent advances in map data structures and s…
Calibrated Keyframe-Segment Selection for Descriptor-Agnostic LiDAR Loop Closure in Repetitive Environments
Jaehyun Kim, Seungwon Choi, Wonseok Kang +1
False LiDAR loop closures can distort pose graphs in repetitive environments, where one query may match several distant places. Genuine revisits, unlike many perceptual aliases, te…
Statistical Uncertainty Learning for Robust Visual-Inertial State Estimation
Seungwon Choi, Donggyu Park, Seo-Yeon Hwang +1
A fundamental challenge in robust visual-inertial odometry (VIO) is to dynamically assess the reliability of sensor measurements. This assessment is crucial for properly weighting…
Efficient Graduated Non-Convexity for Pose Graph Optimization
Wonseok Kang, Jaehyun Kim, Jiseong Chung +2
We propose a novel approach to Graduated Non-Convexity (GNC) and demonstrate its efficacy through its application in robust pose graph optimization, a key component in SLAM backend…