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The increasing demand for real-time high-precision Visual Odometry systems as part of navigation and localization tasks has recently been driving research towards more versatile and scalable solutions. In this paper, we present a novel framework for combining the merits of inertial and visual data from a monocular camera to accumulate estimates of local motion incrementally and reliably reconstruct the trajectory traversed. We demonstrate the robustness and efficiency of our methodology in a scenario with challenging camera dynamics, and present a comprehensive evaluation against ground-truth data. 1
Kneip et al. (Sat,) studied this question.