Yeongkwon Choe — accepted AI-conference papers

2026

MOTCues: 3D Multi-Object Tracking with Birth Prior and Shape Description Informed by Point Cloud Cues

Hanyeol Lee, Yeongkwon Choe, Taeyoon Kim, Chan Gook Park

ICRA 2026poster

Reliable multi-object tracking (MOT) is essential for autonomous systems but remains challenging due to ambiguous object characteristics such as birth, death, and motion models, as well as detector errors including false detections and missed objects. Random finite set (RFS) theory provides a rigoro…

Cited by 0 Scholar ↗

2022

Ensemble Kalman Filter Based LiDAR Odometry for Skewed Point Clouds Using Scan Slicing

Yeongkwon Choe, Jae Hyung Jung, Chan Gook Park

ICRA 2022poster

In the presence of fast motion, point clouds obtained from mechanical spinning LiDAR can be easily distorted due to the slow scanning speed of the LiDAR. Existing LiDAR-only odometry algorithms generally ignore this distortion or compensate by linearly interpolating the estimated relative motion bet…

Cited by 6 Source ↗Scholar ↗