Markó, Norbert and Rózsa, Zoltán and Ballagi, Áron and Szirányi, Tamás (2026) Monocular Ground Normal Prediction for the Road Ahead. IEEE OPEN JOURNAL OF VEHICULAR TECHNOLOGY, 7. pp. 1066-1080. ISSN 2644-1330 10.1109/OJVT.2026.3676610

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Abstract

Robust fusion of monocular and inertial data has the potential to offer a low-cost alternative for ground surface normal prediction ahead, compared to more expensive sensors, such as LiDAR. Yet robust camera-based prediction remains challenging, particularly for steep grades and texture-poor, homogeneous road surfaces. To address these issues, we propose an enhanced monocular camera-IMU fusion pipeline incorporating a lightweight transformer-based feature matcher for improved correspondence accuracy, and robust temporal filtering, using a spherical linear interpolation (SLERP) filter, to enhance consistency and reduce drift. To enable rigorous benchmarking and reproducibility, we also standardize the evaluation protocol and release a novel dataset containing synchronized camera, LiDAR, and IMU-derived pose data, specifically captured across diverse incline and decline scenarios. Extensive continuous validation demonstrates that our method significantly improves both accuracy and temporal stability over existing approaches, setting a new state of the art for robust, continuous ground normal estimation ahead.

Item Type:	Article
Uncontrolled Keywords:	accuracy; PIPELINES; estimation; VECTORS; Telecommunications; Cameras; filtering; Roads; Three-dimensional displays; Transformer; Engineering, Electrical & Electronic; TRANSFORMERS; laser radar; Ground normal prediction; IMU-camera fusion; image-based ground plane prediction; SLERP; road surface normal prediction;
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Machine Perception Research Laboratory
SWORD Depositor:	MTMT Injector
Depositing User:	MTMT Injector
Date Deposited:	03 Jun 2026 07:15
Last Modified:	03 Jun 2026 07:15
URI:	https://eprints.sztaki.hu/id/eprint/11125

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