Bayesian Attitude Estimation with the Matrix Fisher Distribution on SO(3)
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Abstract (arXiv)
This paper focuses on a stochastic formulation of Bayesian attitude estimation on the special orthogonal group. In particular, an exponential probability density model for random matrices, referred to as the matrix Fisher distribution is used to represent the uncertainties of attitude estimates and measurements in a global fashion. Various stochastic properties of the matrix Fisher distribution are derived on the special orthogonal group, and based on these, two types of intrinsic frameworks for Bayesian attitude estimation are constructed. These avoid complexities or singularities of the attitude estimators developed in terms of quaternions. The proposed approaches are particularly useful to deal with large estimation errors or large uncertainties for complex maneuvers to obtain accurate estimates of the attitude.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Oct 2017.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 4; 2024: 4; 2025: 1.
11 papers.
- 2021Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wildcited by 48
- 2023Equivariant Adaptation of Large Pretrained Modelscited by 41
- 2022FisherMatch: Semi-Supervised Rotation Regression via Entropy-based Filteringcited by 16
- 2023SPADES: A Realistic Spacecraft Pose Estimation Dataset using Event Sensingcited by 13
- 2024SimpleEgo: Predicting Probabilistic Body Pose from Egocentric Camerascited by 12
- 2023A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimationcited by 9
- 2023Towards Robust Probabilistic Modeling on SO(3) via Rotation Laplace Distributioncited by 5
- 2024MOSS: Motion-based 3D Clothed Human Synthesis from Monocular Videocited by 1
- 2024Deep Transformer Network for Monocular Pose Estimation of Shipborne Unmanned Aerial Vehiclecited by 1
- 2025Matching the Optimal Denoiser in Point Cloud Diffusion with (Improved) Rotational Alignmentcited by 1
- 2024On the power of data augmentation for head pose estimationcited by 0
- 2025Matching the Optimal Denoiser in Point Cloud Diffusion with (Improved) Rotational Alignment2 Oct 2025
- 2024On the power of data augmentation for head pose estimation7 Jul 2024
- 2024Deep Transformer Network for Monocular Pose Estimation of Shipborne Unmanned Aerial Vehicle13 Jun 2024
- 2024MOSS: Motion-based 3D Clothed Human Synthesis from Monocular Video21 May 2024
- 2024SimpleEgo: Predicting Probabilistic Body Pose from Egocentric Cameras26 Jan 2024
- 2023SPADES: A Realistic Spacecraft Pose Estimation Dataset using Event Sensing9 Nov 2023
- 2023Equivariant Adaptation of Large Pretrained Models2 Oct 2023
- 2023Towards Robust Probabilistic Modeling on SO(3) via Rotation Laplace Distribution17 May 2023
- 2023A Laplace-inspired Distribution on SO(3) for Probabilistic Rotation Estimation3 Mar 2023
- 2022FisherMatch: Semi-Supervised Rotation Regression via Entropy-based Filtering29 Mar 2022
- 2021Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild3 Oct 2021