Ultra-Precision 6DoF Pose Estimation Using 2-D Interpolated Discrete Fourier Transform
Guowei Shi, Zian Mao, Peisen Huang
摘要
Ultra-precision estimation of 6DoF pose is essential in applications such as semiconductor manufacturing and nanoscale manipulation. Conventional vision-based techniques are often hampered by sensitivity to defocus and limited estimation accuracy. In this paper, we propose a novel two-dimensional interpolated Discrete Fourier Transform (2D-IpDFT) method for robust 6DoF pose estimation using periodic patterns. We further develop a mathematical framework that links image parameters-phase and frequency-to 6DoF pose, which is applicable to both orthographic and quasi-orthographic imaging systems. Extensive experiments on a low-cost setup, featuring an industrial camera and an etched checkerboard pattern, demonstrate translation estimation accuracy at the nanometer level and rotation estimation accuracy at the microradian level.
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它引用的顶会 Paper4
- GenFlow: Generalizable Recurrent Flow for 6D Pose Refinement of Novel ObjectsSungphill Moon, Hyeontae Son, Dongcheol Hur, Sangwook KimCVPR 2024 · 被引用 20 次
- Pseudo Flow Consistency for Self-Supervised 6D Object Pose EstimationYang Hai, Rui Song, Jiaojiao Li, David Ferstl 等ICCV 2023 · 被引用 13 次
- GeoReF: Geometric Alignment Across Shape Variation for Category-level Object Pose RefinementLinfang Zheng, Tze Ho Elden Tse, Chen Wang, Yinghan Sun 等CVPR 2024 · 被引用 6 次
- SAM-6D: Segment Anything Model Meets Zero-Shot 6D Object Pose EstimationJiehong Lin, Lihua Liu, Dekun Lu, Kui JiaCVPR 2024
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