Localization through particle filter powered neural network estimated monocular camera poses

Yi Shen; Hao Liu; Xinxin Liu; Wenjing Zhou; Chang Zhou; Yizhou Chen

doi:10.1117/12.3037897

12 September 2024 Localization through particle filter powered neural network estimated monocular camera poses

Yi Shen, Hao Liu, Xinxin Liu, Wenjing Zhou, Chang Zhou, Yizhou Chen

Proceedings Volume 13256, Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024); 132560I (2024) https://doi.org/10.1117/12.3037897
Event: Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), 2024, Anshan, China

Abstract

The reduced cost and computational and calibration requirements of monocular cameras make them ideal positioning sensors for mobile robots, albeit at the expense of any meaningful depth measurement. Solutions proposed by some scholars to this localization problem involve fusing pose estimates from convolutional neural networks (CNNs) with pose estimates from geometric constraints on motion to generate accurate predictions of robot trajectories. However, the distribution of attitude estimation based on CNN is not uniform, resulting in certain translation problems in the prediction of robot trajectories. This paper proposes improving these CNN-based pose estimates by propagating a SE(3) uniform distribution driven by a particle filter. The particles utilize the same motion model used by the CNN, while updating their weights using CNN-based estimates. The results show that while the rotational component of pose estimation does not consistently improve relative to CNN-based estimation, the translational component is significantly more accurate. This factor combined with the superior smoothness of the filtered trajectories shows that the use of particle filters significantly improves the performance of CNN-based localization algorithms.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yi Shen, Hao Liu, Xinxin Liu, Wenjing Zhou, Chang Zhou, and Yizhou Chen "Localization through particle filter powered neural network estimated monocular camera poses", Proc. SPIE 13256, Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), 132560I (12 September 2024); https://doi.org/10.1117/12.3037897

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KEYWORDS

Particles

Particle filters

Pose estimation

Cameras

Error analysis

Neural networks

Covariance

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