A Keyframe Extraction Approach for 3D Videogrammetry Based on Baseline Constraints

Abstract

In this paper, we propose a novel approach for the extraction of high-quality frames to enhance the fidelity of videogrammetry by combining fuzzy frames removal and baseline constraints. We first implement a gradient-based mutual information method to filter out low-quality frames while preserving the integrity of the videos. After frame pose estimation, the geometric properties of the baseline are constrained by three aspects to extract the keyframes: quality of relative orientation, baseline direction, and base to distance ratio. The three-dimensional model is then reconstructed based on these extracted keyframes. Experimental results demonstrate that our approach maintains a strong robustness throughout the aerial triangulation, leading to high levels of reconstruction precision across diverse video scenarios. Compared to other methods, this paper improves the reconstruction accuracy by more than 0.2 mm while simultaneously maintaining the completeness.