POW4R: POint-Wise Full-Velocity Estimation Using 4D Radar-Camera Fusion Beyond Radial Limitations
Year: 2025
Type: article
Abstract: This paper proposes an algorithm for full-velocity estimation by fusing radial velocity vectors obtained from 4D radar with optical flow vectors extracted from camera images. The full-velocity algorithm consists of a preprocessing step and a full-velocity vector estimation step. In preprocessing, radar noise is removed and ego-vehicle velocity estimation is enhanced using a Hampel filter for improved robustness in dynamic environments. In the full-velocity estimation stage, the algorithm estimates full-velocity vectors using a formulation derived from mathematical equations that incorporate multiple constraints. To evaluate the proposed method, an embedded system is implemented on a real vehicle, and datasets are collected under various scenarios. Experimental results show that the proposed algorithm significantly improves object velocity estimation performance. (error rate: baseline 81%$\rightarrow$proposed 31%)
Authors: Hyun-Yong Jeon, Minseong Choi, Yeongseok Lee, Sangyoon Oh, Seunghoon Yang, Keun Ha Choi, Kyung-Soo Kim
Institution: Korea Advanced Institute of Science and Technology
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,645
OpenAlex ID: W4413977932
