# EKFPnP: Extended Kalman Filter for Camera Pose Estimation in a Sequence of Images

arXiv: https://arxiv.org/abs/1906.10324 · HTML: https://mlsanity.com/paper/1906.10324/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Jun 2019.

## Built on by (most cited first, 2 of 2)

- [A PnP Algorithm for Two-Dimensional Pose Estimation](https://mlsanity.com/paper/2312.08488/) (2023)
- [Observability Conditions and Filter Design for Visual Pose Estimation via Dual Quaternions](https://mlsanity.com/paper/2605.02054/) (2026)

## Abstract (arXiv)

In real-world applications the Perspective-n-Point (PnP) problem should generally be applied in a sequence of images which a set of drift-prone features are tracked over time. In this paper, we consider both the temporal dependency of camera poses and the uncertainty of features for the sequential camera pose estimation. Using the Extended Kalman Filter (EKF), a priori estimate of the camera pose is calculated from the camera motion model and then corrected by minimizing the reprojection error of the reference points. Experimental results, using both simulated and real data, demonstrate that the proposed method improves the robustness of the camera pose estimation, in the presence of noise, compared to the state-of-the-art.