← Search

Mingu Jeon

3 accepted papers

2025

Radar-Based NLoS Pedestrian Localization for Darting-Out Scenarios Near Parked Vehicles with Camera-Assisted Point Cloud Interpretation

IROS 2025

The presence of Non-Line-of-Sight (NLoS) blind spots resulting from roadside parking in urban environments poses a significant challenge to road safety, particularly due to the sudden emergence of pedestrians. mmWave technology leverages diffraction and reflection to observe NLoS regions, and recent

Cited by 1SourcecodeScholar
2025

mmWave Radar-Based Non-Line-of-Sight Pedestrian Localization at T-Junctions Utilizing Road Layout Extraction via Camera

IROS 2025

Pedestrians Localization in Non-Line-of-Sight (NLoS) regions within urban environments poses a significant challenge for autonomous driving systems. While mmWave radar has demonstrated potential for detecting objects in such scenarios, the 2D radar point cloud (PCD) data is susceptible to distortion

Cited by 2SourceScholar
2021

Uncertainty-Aware Fast Curb Detection Using Convolutional Networks in Point Clouds

ICRA 2021poster

Curb detection is an essential function of autonomous vehicles in urban areas. However, curbs are difficult to detect in complex urban environments in which many dynamic objects exist. Additionally, curbs appear in a variety of shapes and sizes. Previous studies have been based on the traditional pi…

Cited by 20SourcecodeScholar