Documentdetail
ID kaart
oai:arXiv.org:2409.11854
Onderwerp
Computer Science - Robotics Computer Science - Computer Vision...Auteur
Cheng, Lei Hu, Junpeng Yan, Haodong Gladkova, Mariia Huang, Tianyu Liu, Yun-Hui Cremers, Daniel Li, HaoangCategorie
Computer Science
Jaar
2024
vermelding datum
25-09-2024
Trefwoorden
computer material illumination photometricBeschrijving
Photometric bundle adjustment (PBA) is widely used in estimating the camera pose and 3D geometry by assuming a Lambertian world.
However, the assumption of photometric consistency is often violated since the non-diffuse reflection is common in real-world environments.
The photometric inconsistency significantly affects the reliability of existing PBA methods.
To solve this problem, we propose a novel physically-based PBA method.
Specifically, we introduce the physically-based weights regarding material, illumination, and light path.
These weights distinguish the pixel pairs with different levels of photometric inconsistency.
We also design corresponding models for material estimation based on sequential images and illumination estimation based on point clouds.
In addition, we establish the first SLAM-related dataset of non-Lambertian scenes with complete ground truth of illumination and material.
Extensive experiments demonstrated that our PBA method outperforms existing approaches in accuracy.
;Comment: Accepted to 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)
Cheng, Lei,Hu, Junpeng,Yan, Haodong,Gladkova, Mariia,Huang, Tianyu,Liu, Yun-Hui,Cremers, Daniel,Li, Haoang, 2024, Physically-Based Photometric Bundle Adjustment in Non-Lambertian Environments
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