# Loosely-Coupled Semi-Direct Monocular SLAM

arXiv: https://arxiv.org/abs/1807.10073 · HTML: https://mlsanity.com/paper/1807.10073/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Jul 2018.

## Built on by (most cited first, 8 of 8)

- [Endo-Depth-and-Motion: Reconstruction and Tracking in Endoscopic Videos using Depth Networks and Photometric Constraints](https://mlsanity.com/paper/2103.16525/) (2021)
- [From SLAM to Situational Awareness: Challenges and Survey](https://mlsanity.com/paper/2110.00273/) (2021)
- [What's Wrong with the Absolute Trajectory Error?](https://mlsanity.com/paper/2212.05376/) (2022)
- [H-SLAM: Hybrid Direct-Indirect Visual SLAM](https://mlsanity.com/paper/2306.07363/) (2023)
- [Alignment Scores: Robust Metrics for Multiview Pose Accuracy Evaluation](https://mlsanity.com/paper/2407.20391/) (2024)
- [P3P Made Easy](https://mlsanity.com/paper/2508.01312/) (2025)
- [Inline Photometrically Calibrated Hybrid Visual SLAM](https://mlsanity.com/paper/2409.16810/) (2024)
- [Adaptive Covariance and Quaternion-Focused Hybrid Error-State EKF/UKF for Visual-Inertial Odometry](https://mlsanity.com/paper/2512.17505/) (2025)

## Abstract (arXiv)

We propose a novel semi-direct approach for monocular simultaneous localization and mapping (SLAM) that combines the complementary strengths of direct and feature-based methods. The proposed pipeline loosely couples direct odometry and feature-based SLAM to perform three levels of parallel optimizations: (1) photometric bundle adjustment (BA) that jointly optimizes the local structure and motion, (2) geometric BA that refines keyframe poses and associated feature map points, and (3) pose graph optimization to achieve global map consistency in the presence of loop closures. This is achieved in real-time by limiting the feature-based operations to marginalized keyframes from the direct odometry module. Exhaustive evaluation on two benchmark datasets demonstrates that our system outperforms the state-of-the-art monocular odometry and SLAM systems in terms of overall accuracy and robustness.